{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SVM Classification (Linear)\n",
    "\n",
    "* Well suited for complex, small/medium dataset classification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=inf, cache_size=200, class_weight=None, coef0=0.0,\n",
       "  decision_function_shape=None, degree=3, gamma='auto', kernel='linear',\n",
       "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "  tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Large margin classification:\n",
    "\n",
    "from sklearn.svm import SVC\n",
    "from sklearn import datasets\n",
    "\n",
    "iris = datasets.load_iris()\n",
    "X = iris[\"data\"][:, (2, 3)]  # petal length, petal width\n",
    "y = iris[\"target\"]\n",
    "\n",
    "setosa_or_versicolor = (y == 0) | (y == 1)\n",
    "X = X[setosa_or_versicolor]\n",
    "y = y[setosa_or_versicolor]\n",
    "\n",
    "# SVM Classifier model\n",
    "svm_clf = SVC(kernel=\"linear\", C=float(\"inf\"))\n",
    "svm_clf.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZTUrpJqUMk1LOllL+R0r5n4Lnp0kpG0kpm0opW0opN9jnS7w9Hh61SvW4I/j4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\nUkolkA6wlVJKKaWUSqD/B19QbNfFrLLLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899dca9cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bad models\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "x0 = np.linspace(0, 5.5, 200)\n",
    "pred_1 = 5*x0 - 20\n",
    "pred_2 = x0 - 1.8\n",
    "pred_3 = 0.1 * x0 + 0.5\n",
    "\n",
    "def plot_svc_decision_boundary(svm_clf, xmin, xmax):\n",
    "    w = svm_clf.coef_[0]\n",
    "    b = svm_clf.intercept_[0]\n",
    "\n",
    "    # At the decision boundary, w0*x0 + w1*x1 + b = 0\n",
    "    # => x1 = -w0/w1 * x0 - b/w1\n",
    "    x0 = np.linspace(xmin, xmax, 200)\n",
    "    decision_boundary = -w[0]/w[1] * x0 - b/w[1]\n",
    "\n",
    "    margin = 1/w[1]\n",
    "    gutter_up = decision_boundary + margin\n",
    "    gutter_down = decision_boundary - margin\n",
    "\n",
    "    svs = svm_clf.support_vectors_\n",
    "    plt.scatter(svs[:, 0], svs[:, 1], s=180, facecolors='#FFAAAA')\n",
    "    plt.plot(x0, decision_boundary, \"k-\",  linewidth=2)\n",
    "    plt.plot(x0, gutter_up,         \"k--\", linewidth=2)\n",
    "    plt.plot(x0, gutter_down,       \"k--\", linewidth=2)\n",
    "\n",
    "plt.figure(figsize=(12,2.7))\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.plot(x0, pred_1, \"g--\", linewidth=2)\n",
    "plt.plot(x0, pred_2, \"m-\", linewidth=2)\n",
    "plt.plot(x0, pred_3, \"r-\", linewidth=2)\n",
    "plt.plot(X[:, 0][y==1], X[:, 1][y==1], \"bs\", label=\"Iris-Versicolor\")\n",
    "plt.plot(X[:, 0][y==0], X[:, 1][y==0], \"yo\", label=\"Iris-Setosa\")\n",
    "plt.xlabel(\"Petal length\", fontsize=14)\n",
    "plt.ylabel(\"Petal width\", fontsize=14)\n",
    "plt.legend(loc=\"upper left\", fontsize=14)\n",
    "plt.axis([0, 5.5, 0, 2])\n",
    "\n",
    "plt.subplot(122)\n",
    "plot_svc_decision_boundary(svm_clf, 0, 5.5)\n",
    "plt.plot(X[:, 0][y==1], X[:, 1][y==1], \"bs\")\n",
    "plt.plot(X[:, 0][y==0], X[:, 1][y==0], \"yo\")\n",
    "plt.xlabel(\"Petal length\", fontsize=14)\n",
    "plt.axis([0, 5.5, 0, 2])\n",
    "plt.show()\n",
    "\n",
    "# On left:\n",
    "# dashed line = basically useless decision boundary.\n",
    "# solid lines = OK for this dataset, but no margins. Probably will not work well on new instances.\n",
    "\n",
    "# On right: SVM finds widest possible \"street\" between classes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-2, 2, -2, 2]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2NwAeeOABl3jLli2tXdxefvlllxuJqKgoOnfuDMDMmTNdbhQiIyOJjo6GAwf4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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a61ecf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sensitivity to feature scaling:\n",
    "\n",
    "Xs = np.array([[1, 50], [5, 20], [3, 80], [5, 60]]).astype(np.float64)\n",
    "ys = np.array([0, 0, 1, 1])\n",
    "svm_clf = SVC(kernel=\"linear\", C=100)\n",
    "svm_clf.fit(Xs, ys)\n",
    "\n",
    "plt.figure(figsize=(12,3.2))\n",
    "plt.subplot(121)\n",
    "plt.plot(Xs[:, 0][ys==1], Xs[:, 1][ys==1], \"bo\")\n",
    "plt.plot(Xs[:, 0][ys==0], Xs[:, 1][ys==0], \"ms\")\n",
    "plot_svc_decision_boundary(svm_clf, 0, 6)\n",
    "plt.xlabel(\"$x_0$\", fontsize=20)\n",
    "plt.ylabel(\"$x_1$  \", fontsize=20, rotation=0)\n",
    "plt.title(\"Unscaled\", fontsize=16)\n",
    "plt.axis([0, 6, 0, 90])\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(Xs)\n",
    "svm_clf.fit(X_scaled, ys)\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(X_scaled[:, 0][ys==1], X_scaled[:, 1][ys==1], \"bo\")\n",
    "plt.plot(X_scaled[:, 0][ys==0], X_scaled[:, 1][ys==0], \"ms\")\n",
    "plot_svc_decision_boundary(svm_clf, -2, 2)\n",
    "plt.xlabel(\"$x_0$\", fontsize=20)\n",
    "plt.title(\"Scaled\", fontsize=16)\n",
    "plt.axis([-2, 2, -2, 2])\n",
    "\n",
    "# SVMs are sensitive to feature scaling. \n",
    "# Plot on right has much more robust feature boundary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.50755672, -0.11547005],\n",
       "       [ 0.90453403, -1.5011107 ],\n",
       "       [-0.30151134,  1.27017059],\n",
       "       [ 0.90453403,  0.34641016]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_scaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 5.5, 0, 2]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PVIFCpLaqVauyZcsWDhw4QNeuXbG3t2f16tU4ODgAcP78ee7du2eqrbJlyzJ5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\npZRSSinlRv8fA5yJyZCAgNYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f89a8341630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# \"hard\" margin classification:\n",
    "# - all instances need to be \"out of the street\".\n",
    "# - all instances need to be \"on the right side of the street\".\n",
    "# problem: doable only if data is linearly separable\n",
    "# problem: very sensitive to outliers\n",
    "\n",
    "X_outliers = np.array([[3.4, 1.3], [3.2, 0.8]])\n",
    "y_outliers = np.array([0, 0])\n",
    "Xo1 = np.concatenate([X, X_outliers[:1]], axis=0)\n",
    "yo1 = np.concatenate([y, y_outliers[:1]], axis=0)\n",
    "Xo2 = np.concatenate([X, X_outliers[1:]], axis=0)\n",
    "yo2 = np.concatenate([y, y_outliers[1:]], axis=0)\n",
    "\n",
    "svm_clf2 = SVC(kernel=\"linear\", C=10**9)#float(\"inf\"))\n",
    "svm_clf2.fit(Xo2, yo2)\n",
    "\n",
    "plt.figure(figsize=(12,2.7))\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.plot(Xo1[:, 0][yo1==1], Xo1[:, 1][yo1==1], \"bs\")\n",
    "plt.plot(Xo1[:, 0][yo1==0], Xo1[:, 1][yo1==0], \"yo\")\n",
    "plt.text(0.3, 1.0, \"Impossible!\", fontsize=20, color=\"red\")\n",
    "plt.xlabel(\"Petal length\", fontsize=14)\n",
    "plt.ylabel(\"Petal width\", fontsize=14)\n",
    "plt.annotate(\"Outlier\",\n",
    "             xy=(X_outliers[0][0], X_outliers[0][1]),\n",
    "             xytext=(2.5, 1.7),\n",
    "             ha=\"center\",\n",
    "             arrowprops=dict(facecolor='black', shrink=0.1),\n",
    "             fontsize=16,\n",
    "            )\n",
    "plt.axis([0, 5.5, 0, 2])\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(Xo2[:, 0][yo2==1], Xo2[:, 1][yo2==1], \"bs\")\n",
    "plt.plot(Xo2[:, 0][yo2==0], Xo2[:, 1][yo2==0], \"yo\")\n",
    "plot_svc_decision_boundary(svm_clf2, 0, 5.5)\n",
    "plt.xlabel(\"Petal length\", fontsize=14)\n",
    "plt.annotate(\"Outlier\",\n",
    "             xy=(X_outliers[1][0], X_outliers[1][1]),\n",
    "             xytext=(3.2, 0.08),\n",
    "             ha=\"center\",\n",
    "             arrowprops=dict(facecolor='black', shrink=0.1),\n",
    "             fontsize=16,\n",
    "            )\n",
    "plt.axis([0, 5.5, 0, 2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.50755672, -0.11547005],\n",
       "       [ 0.90453403, -1.5011107 ],\n",
       "       [-0.30151134,  1.27017059],\n",
       "       [ 0.90453403,  0.34641016]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_scaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# soluton to \"hard margins\" problem:\n",
    "# control hardness with C hyperparameter\n",
    "\n",
    "from sklearn import datasets\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.svm import LinearSVC\n",
    "\n",
    "iris = datasets.load_iris()\n",
    "X = iris[\"data\"][:, (2, 3)]  # petal length, petal width\n",
    "y = (iris[\"target\"] == 2).astype(np.float64)  # Iris-Virginica\n",
    "\n",
    "scaler = StandardScaler()\n",
    "svm_clf1 = LinearSVC(C=100, loss=\"hinge\")\n",
    "svm_clf2 = LinearSVC(C=1, loss=\"hinge\")\n",
    "\n",
    "scaled_svm_clf1 = Pipeline((\n",
    "        (\"scaler\", scaler),\n",
    "        (\"linear_svc\", svm_clf1),\n",
    "    ))\n",
    "scaled_svm_clf2 = Pipeline((\n",
    "        (\"scaler\", scaler),\n",
    "        (\"linear_svc\", svm_clf2),\n",
    "    ))\n",
    "\n",
    "scaled_svm_clf1.fit(X, y)\n",
    "scaled_svm_clf2.fit(X, y)\n",
    "\n",
    "scaled_svm_clf2.predict([[5.5, 1.7]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.50755672, -0.11547005],\n",
       "       [ 0.90453403, -1.5011107 ],\n",
       "       [-0.30151134,  1.27017059],\n",
       "       [ 0.90453403,  0.34641016]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_scaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Convert to unscaled parameters\n",
    "b1 = svm_clf1.decision_function([-scaler.mean_ / scaler.scale_])\n",
    "b2 = svm_clf2.decision_function([-scaler.mean_ / scaler.scale_])\n",
    "w1 = svm_clf1.coef_[0] / scaler.scale_\n",
    "w2 = svm_clf2.coef_[0] / scaler.scale_\n",
    "svm_clf1.intercept_ = np.array([b1])\n",
    "svm_clf2.intercept_ = np.array([b2])\n",
    "svm_clf1.coef_ = np.array([w1])\n",
    "svm_clf2.coef_ = np.array([w2])\n",
    "\n",
    "# Find support vectors (LinearSVC does not do this automatically)\n",
    "t = y * 2 - 1\n",
    "support_vectors_idx1 = (t * (X.dot(w1) + b1) < 1).ravel()\n",
    "support_vectors_idx2 = (t * (X.dot(w2) + b2) < 1).ravel()\n",
    "svm_clf1.support_vectors_ = X[support_vectors_idx1]\n",
    "svm_clf2.support_vectors_ = X[support_vectors_idx2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[4, 6, 0.8, 2.8]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Xr3PmzBkCHW1HqSrG0qYPtlruy551OwJHi9kFKaVo3LgxjRs3Nh2bNm0ajz/+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\n7dq14+TJk3zwwQf06tWLTp0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Wmri4OA4fPsyIESPQWtO2bVuOHDmCt7c3Q4YMISIigoED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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899dc89b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,3.2))\n",
    "plt.subplot(121)\n",
    "plt.plot(X[:, 0][y==1], X[:, 1][y==1], \"g^\", label=\"Iris-Virginica\")\n",
    "plt.plot(X[:, 0][y==0], X[:, 1][y==0], \"bs\", label=\"Iris-Versicolor\")\n",
    "plot_svc_decision_boundary(svm_clf1, 4, 6)\n",
    "plt.xlabel(\"Petal length\", fontsize=14)\n",
    "plt.ylabel(\"Petal width\", fontsize=14)\n",
    "plt.legend(loc=\"upper left\", fontsize=14)\n",
    "plt.title(\"$C = {}$\".format(svm_clf1.C), fontsize=16)\n",
    "plt.axis([4, 6, 0.8, 2.8])\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(X[:, 0][y==1], X[:, 1][y==1], \"g^\")\n",
    "plt.plot(X[:, 0][y==0], X[:, 1][y==0], \"bs\")\n",
    "plot_svc_decision_boundary(svm_clf2, 4, 6)\n",
    "plt.xlabel(\"Petal length\", fontsize=14)\n",
    "plt.title(\"$C = {}$\".format(svm_clf2.C), fontsize=16)\n",
    "plt.axis([4, 6, 0.8, 2.8])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SVM Classification (Non-Linear)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a7149b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# some (most?) datasets are not linearly separable. simple example below.\n",
    "\n",
    "X1D = np.linspace(-4, 4, 9).reshape(-1, 1)\n",
    "\n",
    "X2D = np.c_[X1D, X1D**2] # adds 2nd, non-linear dimension.\n",
    "\n",
    "y = np.array([0, 0, 1, 1, 1, 1, 1, 0, 0])\n",
    "\n",
    "plt.figure(figsize=(10, 4))\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.grid(True, which='both')\n",
    "plt.axhline(y=0, color='k')\n",
    "plt.plot(X1D[:, 0][y==0], np.zeros(4), \"bs\")\n",
    "plt.plot(X1D[:, 0][y==1], np.zeros(5), \"g^\")\n",
    "plt.gca().get_yaxis().set_ticks([])\n",
    "plt.xlabel(r\"$x_1$\", fontsize=20)\n",
    "plt.axis([-4.5, 4.5, -0.2, 0.2])\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.grid(True, which='both')\n",
    "plt.axhline(y=0, color='k')\n",
    "plt.axvline(x=0, color='k')\n",
    "plt.plot(X2D[:, 0][y==0], X2D[:, 1][y==0], \"bs\")\n",
    "plt.plot(X2D[:, 0][y==1], X2D[:, 1][y==1], \"g^\")\n",
    "plt.xlabel(r\"$x_1$\", fontsize=20)\n",
    "plt.ylabel(r\"$x_2$\", fontsize=20, rotation=0)\n",
    "plt.gca().get_yaxis().set_ticks([0, 4, 8, 12, 16])\n",
    "plt.plot([-4.5, 4.5], [6.5, 6.5], \"r--\", linewidth=3)\n",
    "plt.axis([-4.5, 4.5, -1, 17])\n",
    "\n",
    "plt.subplots_adjust(right=1)\n",
    "\n",
    "#save_fig(\"higher_dimensions_plot\", tight_layout=False)\n",
    "plt.show()\n",
    "\n",
    "# result: adding 2nd dimension (on right) makes dataset linearly separable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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eTuDX3f1Y9PhfAn8MrHf3TwYMUSR1qpmIpMzdtwF/T/NiaB8DMLNP00wkG4Hr\nwkUnkg3VTEQyYGZn0lyXaz/wl8DfAI8C/8WbF8sSqRTVTEQy4O4vAn8NnE0zkTwJrJydSMzsUjPb\nZGb7or6UP8w9WJEUKJmIZOfVtvvXuvvPO2yzkObS/TcAv8glKpEMKJmIZMDM/gD4C5rNXNBMFnO4\n+2Z3/7S7PwQczys+kbQpmYikLLrM6X00axy/QXNU1yfMbFnIuESypGQikiIzuwR4iOYFnD7k7q8C\nf0LzEtlfCBmbSJaUTERSYmbnAY8Ah4Hf9ehyrFET1lPACjP7rYAhimRGyUQkBWb2XmALzcuhfsjd\nfzJrk5ujf/8818BEcjI/dAAiVeDuu4HRHs9vpXn9b5FKUjIRCcjMFgLvjf6cB5wVNZcddPefhYtM\nZDCaAS8SkJmNARMdnrrf3f8w32hEhqdkIiIiiakDXkREElMyERGRxJRMREQkMSUTERFJTMlEREQS\nUzIREZHElExERCQxJRMREUns/wONji5/tsi2YAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a3a00b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# test on \"moons\" dataset\n",
    "\n",
    "from sklearn.datasets import make_moons\n",
    "X, y = make_moons(n_samples=100, noise=0.15, random_state=42)\n",
    "\n",
    "def plot_dataset(X, y, axes):\n",
    "    plt.plot(X[:, 0][y==0], X[:, 1][y==0], \"bs\")\n",
    "    plt.plot(X[:, 0][y==1], X[:, 1][y==1], \"g^\")\n",
    "    plt.axis(axes)\n",
    "    plt.grid(True, which='both')\n",
    "    plt.xlabel(r\"$x_1$\", fontsize=20)\n",
    "    plt.ylabel(r\"$x_2$\", fontsize=20, rotation=0)\n",
    "\n",
    "plot_dataset(X, y, [-1.5, 2.5, -1, 1.5])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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/A8emF1FnJVDH0fZWht9sp2ZbObNG32vrLC+rfz9zrcwv5nkirXuo6thO14b3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\nCZEUDZMAi7b3UtP2AuXVOzn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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a39bc88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# do this in Scikit with a Pipeline. Contents:\n",
    "# 1) Polynomial Features\n",
    "# 2) StandardScaler\n",
    "# 3) LinearSVC\n",
    "\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "\n",
    "polynomial_svm_clf = Pipeline((\n",
    "        (\"poly_features\", PolynomialFeatures(degree=3)),\n",
    "        (\"scaler\", StandardScaler()),\n",
    "        (\"svm_clf\", LinearSVC(C=10, loss=\"hinge\"))\n",
    "    ))\n",
    "\n",
    "polynomial_svm_clf.fit(X, y)\n",
    "\n",
    "def plot_predictions(clf, axes):\n",
    "    x0s = np.linspace(axes[0], axes[1], 100)\n",
    "    x1s = np.linspace(axes[2], axes[3], 100)\n",
    "    x0, x1 = np.meshgrid(x0s, x1s)\n",
    "    X = np.c_[x0.ravel(), x1.ravel()]\n",
    "    y_pred = clf.predict(X).reshape(x0.shape)\n",
    "    y_decision = clf.decision_function(X).reshape(x0.shape)\n",
    "    plt.contourf(x0, x1, y_pred, cmap=plt.cm.brg, alpha=0.2)\n",
    "    plt.contourf(x0, x1, y_decision, cmap=plt.cm.brg, alpha=0.1)\n",
    "\n",
    "plot_predictions(polynomial_svm_clf, [-1.5, 2.5, -1, 1.5])\n",
    "plot_dataset(X, y, [-1.5, 2.5, -1, 1.5])\n",
    "\n",
    "#save_fig(\"moons_polynomial_svc_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solving polynomial-feature problems (aka combinatorial explosion) via the kernel trick\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SqEWrUqhmqViCN5HMpxIm0NXF8zPndcWQkzKcL/wm1B6m/ODTdK446vhhKtmQQjULxRi+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\nuSmFqkgp2HaMOb2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/ChwBfppnO4UQKRSy8M5qofYwgWAnh6qP5X2NdPtHtvY8k/Gx8Tv4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\nNOGXjRSp7ouE+imv81aOeFX95lsYbD1NycHT9Os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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f89996c9780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "\n",
    "# train SVM classifier using 3rd-degree polynomial kernel\n",
    "poly_kernel_svm_clf = Pipeline((\n",
    "    (\"scaler\", StandardScaler()),\n",
    "    (\"svm_clf\", SVC(\n",
    "        kernel=\"poly\", degree=3, coef0=1, C=5))))\n",
    "\n",
    "# train SVM classifier using 10th-degree polynomial kernel (for comparison)\n",
    "poly100_kernel_svm_clf = Pipeline((\n",
    "        (\"scaler\", StandardScaler()),\n",
    "        (\"svm_clf\", SVC(kernel=\"poly\", degree=10, coef0=100, C=5))\n",
    "    ))\n",
    "\n",
    "poly_kernel_svm_clf.fit(X, y)\n",
    "poly100_kernel_svm_clf.fit(X, y)\n",
    "\n",
    "plt.figure(figsize=(11, 4))\n",
    "\n",
    "plt.subplot(121)\n",
    "plot_predictions(poly_kernel_svm_clf, [-1.5, 2.5, -1, 1.5])\n",
    "plot_dataset(X, y, [-1.5, 2.5, -1, 1.5])\n",
    "plt.title(r\"$d=3, r=1, C=5$\", fontsize=18)\n",
    "\n",
    "plt.subplot(122)\n",
    "plot_predictions(poly100_kernel_svm_clf, [-1.5, 2.5, -1, 1.5])\n",
    "plot_dataset(X, y, [-1.5, 2.5, -1, 1.5])\n",
    "plt.title(r\"$d=10, r=100, C=5$\", fontsize=18)\n",
    "\n",
    "#save_fig(\"moons_kernelized_polynomial_svc_plot\")\n",
    "plt.show()\n",
    "\n",
    "# left: 3rd-degree polynomial; right: 10th-degree polynomial.\n",
    "# if overfitting, reduce polynomial degree. if underfitting, bump it up.\n",
    "# \"coef0\": controls high- vs low-degree polynomial influence."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding Similarity Features\n",
    "\n",
    "* **similarity function**: measures how much an instance resembles specified landmark."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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/svllMzuOV/nyqS8ZUHeAU871zDOwfz8EBDjldMKmRQv4+2/4/XezkwghhBCZ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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a5a6748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define similarity function to be Gaussian Radial Basis Function (RBF)\n",
    "# equals 0 (far away) to 1 (at landmark)\n",
    "\n",
    "def gaussian_rbf(x, landmark, gamma):\n",
    "    return np.exp(-gamma * np.linalg.norm(x - landmark, axis=1)**2)\n",
    "\n",
    "gamma = 0.3\n",
    "\n",
    "x1s = np.linspace(-4.5, 4.5, 200).reshape(-1, 1)\n",
    "x2s = gaussian_rbf(x1s, -2, gamma)\n",
    "x3s = gaussian_rbf(x1s, 1, gamma)\n",
    "\n",
    "XK = np.c_[gaussian_rbf(X1D, -2, gamma), gaussian_rbf(X1D, 1, gamma)]\n",
    "yk = np.array([0, 0, 1, 1, 1, 1, 1, 0, 0])\n",
    "\n",
    "plt.figure(figsize=(11, 4))\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.grid(True, which='both')\n",
    "plt.axhline(y=0, color='k')\n",
    "plt.scatter(x=[-2, 1], y=[0, 0], s=150, alpha=0.5, c=\"red\")\n",
    "plt.plot(X1D[:, 0][yk==0], np.zeros(4), \"bs\")\n",
    "plt.plot(X1D[:, 0][yk==1], np.zeros(5), \"g^\")\n",
    "plt.plot(x1s, x2s, \"g--\")\n",
    "plt.plot(x1s, x3s, \"b:\")\n",
    "plt.gca().get_yaxis().set_ticks([0, 0.25, 0.5, 0.75, 1])\n",
    "plt.xlabel(r\"$x_1$\", fontsize=20)\n",
    "plt.ylabel(r\"Similarity\", fontsize=14)\n",
    "plt.annotate(r'$\\mathbf{x}$',\n",
    "             xy=(X1D[3, 0], 0),\n",
    "             xytext=(-0.5, 0.20),\n",
    "             ha=\"center\",\n",
    "             arrowprops=dict(facecolor='black', shrink=0.1),\n",
    "             fontsize=18,\n",
    "            )\n",
    "plt.text(-2, 0.9, \"$x_2$\", ha=\"center\", fontsize=20)\n",
    "plt.text(1, 0.9, \"$x_3$\", ha=\"center\", fontsize=20)\n",
    "plt.axis([-4.5, 4.5, -0.1, 1.1])\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.grid(True, which='both')\n",
    "plt.axhline(y=0, color='k')\n",
    "plt.axvline(x=0, color='k')\n",
    "plt.plot(XK[:, 0][yk==0], XK[:, 1][yk==0], \"bs\")\n",
    "plt.plot(XK[:, 0][yk==1], XK[:, 1][yk==1], \"g^\")\n",
    "plt.xlabel(r\"$x_2$\", fontsize=20)\n",
    "plt.ylabel(r\"$x_3$  \", fontsize=20, rotation=0)\n",
    "plt.annotate(r'$\\phi\\left(\\mathbf{x}\\right)$',\n",
    "             xy=(XK[3, 0], XK[3, 1]),\n",
    "             xytext=(0.65, 0.50),\n",
    "             ha=\"center\",\n",
    "             arrowprops=dict(facecolor='black', shrink=0.1),\n",
    "             fontsize=18,\n",
    "            )\n",
    "plt.plot([-0.1, 1.1], [0.57, -0.1], \"r--\", linewidth=3)\n",
    "plt.axis([-0.1, 1.1, -0.1, 1.1])\n",
    "    \n",
    "plt.subplots_adjust(right=1)\n",
    "\n",
    "#save_fig(\"kernel_method_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Phi(-1.0, -2) = [ 0.74081822]\n",
      "Phi(-1.0, 1) = [ 0.30119421]\n"
     ]
    }
   ],
   "source": [
    "x1_example = X1D[3, 0]\n",
    "for landmark in (-2, 1):\n",
    "    k = gaussian_rbf(np.array([[x1_example]]), np.array([[landmark]]), gamma)\n",
    "    print(\"Phi({}, {}) = {}\".format(x1_example, landmark, k))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using a Gaussian RBF Kernel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SipLuYyAjcRsXzDuAjsYAKufbZxqb0NN67q0WeHZuwvC6kwhe+VlUzNVPbGrB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\nCIIgCF9CQpUgCIIgCILwJf8f2Z1Pv+cLroAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a5d3898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rbf_kernel_svm_clf = Pipeline((\n",
    "        (\"scaler\", StandardScaler()),\n",
    "        (\"svm_clf\", SVC(kernel=\"rbf\", gamma=5, C=0.001))\n",
    "    ))\n",
    "rbf_kernel_svm_clf.fit(X, y)\n",
    "\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "gamma1, gamma2 = 0.1, 5\n",
    "C1, C2 = 0.001, 1000\n",
    "hyperparams = (gamma1, C1), (gamma1, C2), (gamma2, C1), (gamma2, C2)\n",
    "\n",
    "svm_clfs = []\n",
    "for gamma, C in hyperparams:\n",
    "    rbf_kernel_svm_clf = Pipeline((\n",
    "            (\"scaler\", StandardScaler()),\n",
    "            (\"svm_clf\", SVC(kernel=\"rbf\", gamma=gamma, C=C))\n",
    "        ))\n",
    "    rbf_kernel_svm_clf.fit(X, y)\n",
    "    svm_clfs.append(rbf_kernel_svm_clf)\n",
    "\n",
    "plt.figure(figsize=(11, 7))\n",
    "\n",
    "for i, svm_clf in enumerate(svm_clfs):\n",
    "    plt.subplot(221 + i)\n",
    "    plot_predictions(svm_clf, [-1.5, 2.5, -1, 1.5])\n",
    "    plot_dataset(X, y, [-1.5, 2.5, -1, 1.5])\n",
    "    gamma, C = hyperparams[i]\n",
    "    plt.title(r\"$\\gamma = {}, C = {}$\".format(gamma, C), fontsize=16)\n",
    "\n",
    "#save_fig(\"moons_rbf_svc_plot\")\n",
    "plt.show()\n",
    "\n",
    "# below: model trained with different values of gamma and C.\n",
    "# GAMMA:\n",
    "# bigger gamma = narrower bell curve, so each instance's area of influence = smaller.\n",
    "# smaller gamma: bigger bell curve = smoother decision boundary."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Computational Complexity\n",
    "\n",
    "* **LinearSVC** class: based on *liblinear* library. Doesn't support kernel trick. Scales linearly to #instances and #features; training complexity ~O(mxn).\n",
    "* **SVC** class: based on *libsvm* library. Does support kernel trick. Training complexity is O(m^2xn) to O(m^3xn) = MUCH slower on larger training datasets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SVM Regression (Linear & Non-Linear)\n",
    "\n",
    "* Objectives: 1) fit max #instances *on* the street; 2) find min #margin violations (instances \"off\" the street\").\n",
    "* Width controlled by epsilon hyperparameter.\n",
    "* Below: random linear dataset. two training results with different vals of epsilon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.svm import LinearSVR\n",
    "import numpy.random as rnd\n",
    "\n",
    "rnd.seed(42)\n",
    "m = 50\n",
    "X = 2 * rnd.rand(m, 1)\n",
    "y = (4 + 3 * X + rnd.randn(m, 1)).ravel()\n",
    "\n",
    "svm_reg1 = LinearSVR(epsilon=1.5)\n",
    "svm_reg2 = LinearSVR(epsilon=0.5)\n",
    "svm_reg1.fit(X, y)\n",
    "svm_reg2.fit(X, y)\n",
    "\n",
    "def find_support_vectors(svm_reg, X, y):\n",
    "    y_pred = svm_reg.predict(X)\n",
    "    off_margin = (np.abs(y - y_pred) >= svm_reg.epsilon)\n",
    "    return np.argwhere(off_margin)\n",
    "\n",
    "svm_reg1.support_ = find_support_vectors(svm_reg1, X, y)\n",
    "svm_reg2.support_ = find_support_vectors(svm_reg2, X, y)\n",
    "\n",
    "eps_x1 = 1\n",
    "eps_y_pred = svm_reg1.predict([[eps_x1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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4ucUwceIEZs0aQXCw8TfvgYFQqlTm6xwdk1iwoIJJjsqdO3fo3r07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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a4c93c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_svm_regression(svm_reg, X, y, axes):\n",
    "    x1s = np.linspace(axes[0], axes[1], 100).reshape(100, 1)\n",
    "    y_pred = svm_reg.predict(x1s)\n",
    "    plt.plot(x1s, y_pred, \"k-\", linewidth=2, label=r\"$\\hat{y}$\")\n",
    "    plt.plot(x1s, y_pred + svm_reg.epsilon, \"k--\")\n",
    "    plt.plot(x1s, y_pred - svm_reg.epsilon, \"k--\")\n",
    "    plt.scatter(X[svm_reg.support_], y[svm_reg.support_], s=180, facecolors='#FFAAAA')\n",
    "    plt.plot(X, y, \"bo\")\n",
    "    plt.xlabel(r\"$x_1$\", fontsize=18)\n",
    "    plt.legend(loc=\"upper left\", fontsize=18)\n",
    "    plt.axis(axes)\n",
    "\n",
    "plt.figure(figsize=(9, 4))\n",
    "plt.subplot(121)\n",
    "plot_svm_regression(svm_reg1, X, y, [0, 2, 3, 11])\n",
    "plt.title(r\"$\\epsilon = {}$\".format(svm_reg1.epsilon), fontsize=18)\n",
    "plt.ylabel(r\"$y$\", fontsize=18, rotation=0)\n",
    "#plt.plot([eps_x1, eps_x1], [eps_y_pred, eps_y_pred - svm_reg1.epsilon], \"k-\", linewidth=2)\n",
    "plt.annotate(\n",
    "        '', xy=(eps_x1, eps_y_pred), xycoords='data',\n",
    "        xytext=(eps_x1, eps_y_pred - svm_reg1.epsilon),\n",
    "        textcoords='data', arrowprops={'arrowstyle': '<->', 'linewidth': 1.5}\n",
    "    )\n",
    "plt.text(0.91, 5.6, r\"$\\epsilon$\", fontsize=20)\n",
    "plt.subplot(122)\n",
    "plot_svm_regression(svm_reg2, X, y, [0, 2, 3, 11])\n",
    "plt.title(r\"$\\epsilon = {}$\".format(svm_reg2.epsilon), fontsize=18)\n",
    "#save_fig(\"svm_regression_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Use kernel-ized SVM model to handle nonlinear regression jobs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVR(C=0.01, cache_size=200, coef0=0.0, degree=2, epsilon=0.1, gamma='auto',\n",
       "  kernel='poly', max_iter=-1, shrinking=True, tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.svm import SVR\n",
    "\n",
    "# random quadratic training set.\n",
    "rnd.seed(42)\n",
    "m = 100\n",
    "X = 2 * rnd.rand(m, 1) - 1\n",
    "y = (0.2 + 0.1 * X + 0.5 * X**2 + rnd.randn(m, 1)/10).ravel()\n",
    "\n",
    "svm_poly_reg1 = SVR(kernel=\"poly\", degree=2, C=100, epsilon=0.1)\n",
    "svm_poly_reg2 = SVR(kernel=\"poly\", degree=2, C=0.01, epsilon=0.1)\n",
    "svm_poly_reg1.fit(X, y)\n",
    "svm_poly_reg2.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dniI1FfLz84uT28XFxSEqS6hwbq7m12Kd++L0aU3QT5+2zYWxcSNs2QLffKM5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\nh8PhcDguyf8DVi4ANQd6MdoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a337dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 4))\n",
    "plt.subplot(121)\n",
    "plot_svm_regression(svm_poly_reg1, X, y, [-1, 1, 0, 1])\n",
    "plt.title(r\"$degree={}, C={}, \\epsilon = {}$\".format(svm_poly_reg1.degree, svm_poly_reg1.C, svm_poly_reg1.epsilon), fontsize=18)\n",
    "plt.ylabel(r\"$y$\", fontsize=18, rotation=0)\n",
    "plt.subplot(122)\n",
    "plot_svm_regression(svm_poly_reg2, X, y, [-1, 1, 0, 1])\n",
    "plt.title(r\"$degree={}, C={}, \\epsilon = {}$\".format(svm_poly_reg2.degree, svm_poly_reg2.C, svm_poly_reg2.epsilon), fontsize=18)\n",
    "#save_fig(\"svm_with_polynomial_kernel_plot\")\n",
    "plt.show()\n",
    "\n",
    "# left: little regularization (large C)\n",
    "# right: much more regularization (little C)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Under the Hood\n",
    "\n",
    "* conventions: b = bias term; w = feature weights vector."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "iris = datasets.load_iris()\n",
    "X = iris[\"data\"][:, (2, 3)]  # petal length, petal width\n",
    "y = (iris[\"target\"] == 2).astype(np.float64)  # Iris-Virginica"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wqU99Cu973/ugVCrxyCOP4I477khauboTSPXxvffeixtvvBGvvfYaXnrppYy2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\nWFigua15eXngcDgwmUzweDzw+/0oKiqimqV0sLS0BKVSiaqqqoRWCyRKjc/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X5XLhpZde\ngslkwi233AKZTBbXT49Mt7JJTCgUilvFSvdYyBTsKdW6urotbYgcnYFrsViwvr6OcDiM3NxciMVi\nTExMQCgUorOzE1qtFl/72tfQ2dmJRx55JKM8421sKWyTva2Gi8nHJVmiy8vL2LVrV8Rd9tmzZ9HW\n1oasrKyESRfnzp2jfmGhUAiFhYWoqamJqSgRwshegKampqBWq6FQKFBVVRWxMMVrp7G/zzZGlcvl\nST9jdMXD7/djenoa2dnZ6OzshM1mg9lsRklJCaRSKbV5Ic8nFjEk2/bs2bNYX19HZ2cnqqqqIojg\nZovGxUaZsY2L8/PzsbS0RCtK1dXVSd+fVLXYVal0QIyqGxsbUV9fn9ZrSdze0tIS6uvrIRAIKIHJ\ny8tDSUkJ8vPzE+oq2frGdDOOgbcr15latLDfv7e3FxaLBUajkVbSN9uX7MzcZENAyTA3N4eJiQlI\npVKUlJREDCiR6D12FSt6m6xWK9566y243W46MFJcXBxjVJxoUCYQCGB8fBxWqxVNTU1UY5dKIg2B\n3W6HUqmkub+JbubiVShJ0sjU1BREIhEOHTq0qd4yGuRcjo4+CwY38m+jfe4uVevR5/NRL8u6urq0\nBsiuNrxeL1QqFVwuFxoaGiCRSOhwyO9+9zv8/ve/x/T0NFZWVlBbW4vdu3ejtbUVLS0t6Ovr29RO\naTOkknxx4sQJ3HbbbXQteN/73oevfvWrAIBXXnkFR44cQSgUwr333ouHHnroorbnLwjbmr0/J8zM\nzGB5eRnNzc0x7RSBQACfzxcxUcteQCYmJjA6OgqxWIwdO3YkrcpwOBwIBAL6c6IP2rVrV9oTrCaT\nCUNDQ6ivr8euXbsokUyFJLrdbszOzsLv9yM/Px+Dg4MoKChAYWEhvF4vba0kAjFOrqurQygUwsLC\nAgKBAPx+PzU5JvYwYrGYamdEIhGcTifOnz8PiUSCuro6ap+QSmuJbVzc3t6O9fV1zMzMoKqqCnv2\n7Nn0d7hcLpw9exYikQjd3d1pEz29Xg+lUgmpVJo20QM2jjOXy4W+vj6q91EoFCgrK6MVGKvViqWl\npRhrjtzcXMzNzcHhcKCnpydtohcOh3Hu3Dl4PB709vamTfTIvrdarSgtLaWDIekQZhK71N7enhHR\nW1lZgVKphEKhiKnIkil1Ql7IcAjRYpFJ4TfffBNutxvvec97UFtbm/YxMDExgbKyMhw+fDhGMkES\naRINxASDQdrClslk6OjoAPC2hyTpEkSfwwBoqo3dbgcAiMVi7NmzJ22iB2xch0gOcDQJ8fv9lPyx\nLU4EAkEMkRYKhSmRNbYhslwuv6YMkdnbrlAo0NLSQredyDfeeustrK2t4Sc/+Qn6+/vp9XV6ehoD\nAwMoKirCvn37Lmo7+Hw+vvOd70QkXxw+fDjGDPnAgQP47W9/G/G9UCiEBx54AK+++iqkUil6e3tx\n6623JjRS3kb62CZ7VxDEoDhdqNVqqFQq1NbWoq6ujn6fnXQxMTEBDocTMY3J4/EwOjqKCxcuoLOz\nE4cOHUpr4VhdXcXU1BTKysrSPukcDgfOnj2LvLw89Pb2ptV+CQaDePPNNyEUCtHY2Eg98dgGv9EE\nkb3wECF1b28vzQyORyq9Xi8cDgeMRiM8Hg+tCur1emRnZ6OlpYVqAsl7J9Jaka8XFxfpZCp7+pDP\n58PhcMRUSKIHd4aHhwEgrYQKAjIMUlxcjPb29rReC2wcZ2Tfra2txRAloVAYo+thp12MjIxQoqnR\naLC2thY38iwRJicnYTKZqL1MuhgfH8e5c+dQXFxMLXfSOd51Oh00Gk3ambkEZKAlOjOYgEyq5uTk\nRBBJhmHgcDigUqlw8uRJMAyDtrY2GAwG2Gy2tPRsWq2W5gbH08ayE2niIRAI/ClDt5LKDzZDIBCA\nRqOhA1RkqKm2tjajG47NIBQKUVRUlNAr0Ol0Ym1tDRqNhso7ovVs5FgMhUJYXFzEysoKampqsGfP\nnqs2hZouwuEwzaqtrq6O2XaLxYLvfve7OHHiBL7yla/g1ltvpT/Pzc1FV1cXurq6Ltn2pJt8wQYp\nChBrow984AN46aWXtsneJcQ22dviYBMuMtEHICLpgu1/5na7YTQaMTs7C6PRiIWFBZSUlKCiogJL\nS0u0lbkZkbBYLDh//jwKCgrSbmN6vV4MDQ2Bz+enTfTsdjuOHz8Og8GAv/qrv0Jra2tC8+J4n0Gv\n18PlcqGnpydlrRs7reLUqVP0zj4QCFBRPlk0iMkwj8ejOizinq/VajE6OkrbziRlxGAwJHxvopni\ncrmYn5+H2+1GZ2cn5ubm4rbK4mki+Xw+fD4fRkZGkJ2dnbZRNbBBdF599VUIhULceOONKC8vT+l3\n8Hg8iMViWCwWMAyDd77znWhtbaXpDOzgea/XG5HUwF54NRoN1XWmOsBD4Pf7cebMGYyMjKCrqwsH\nDx5M+/ObTCZMTk6ipKQk7rDTZvB6vTh79iyysrLSqsiSoZHV1VXYbDbIZDL09vairKwsRpC/vr5O\nrSXYkV3k3/X1dUxNTaG0tDQjjR0haW63G3v27NmU6LGJklQqxYEDB+B0OnH69GlanbmSEAgEkEgk\nMfq6YDBI28Hr6+vQ6XTwer205S2RSKBQKCAWi6+Jah7DMFhdXYVGo0F5eXlMx8Dr9eInP/kJfv7z\nn+Mf/uEf8M1vfjOj4ZyLgUajwblz57B3796Ynw0MDFBpzRNPPIG2tjbo9fqIdA6pVIrBwcErucl/\n9tgme1cQ6V5ILBYLzp07B4lEQtugRJNHfh/5ncQDSqfTQSAQoLq6Gg6HA319fejp6aGLBsmd9Pv9\nEdoXsvjy+Xy4XC6MjIwgKysr7QzQYDAYkXCRikUB8f7TaDRQKpXgcDi47bbbIJPJ0tpf7MpWOp5o\nZGGempoCh8PB4cOHY6oG7IWXLSQn1RqDwQCz2YzDhw/jxhtvpNOfm7Wtyf+npqbg9XpRX18PkUgE\nu90e8ZxkCAQCmJmZQSgUQltbG06cOBF3CCZeJTIQCECpVOL8+fOora3FzTffDJFIRCdNUyEta2tr\nlGQQosTj8VBQUBAzIc1eeM1mM7RaLVZXVzE/P4+qqiqIRCKYzeaUUgb8fj80Gg3UajXW1tbQ39+P\nvXv3pn2eOZ1OjI6OIjc3N21rHmCD9IyMjCAYDKK/vz+limwwGMTi4iJWV1chlUpRVFQEq9WK1tZW\nOiXMTmuIrgT6fD56HC4uLsJkMuHChQvIzc1FbW0tVlZWUrLmYGN6ehomkwkdHR1JK6tEk7e0tISK\nigpKNvx+P86ePQs+nx9h1H61wefz6bFIiJJWq0VZWRl27NhBK/yrq6txPSvJpPrVrvixff4KCgrQ\n3d0dcayFQiH88pe/xFNPPYU777wTZ86cSVsKcSmQLPmiq6sLOp0OeXl5OH78OP76r/8a8/PzV3wb\n/xKxTfa2KAjhEolEtNQeCoUowSMLEjFmXlpagkQioWVvYvnR29tLDWOj73iJ9sXpdGJ5eZnacszN\nzUEgEOAd73hHWno14snldDrR3d296Sg/22dOJBLRdotcLk+b6DmdTpw9ezbjytaFCxewvr6OXbt2\nxRA9IP7Ca7VaoVKpKImuqqpCZWUlRkdHASCidZTM325+fh75+fno7u5O2PZKlHgRCAQwMjKCsrIy\ndHZ2IicnJy659Hq9Ed/3eDxU72S1Wqlx65kzZ2I+d6Kpay6XC5/Ph4mJCeTm5qK+vh5LS0txn8/+\nP5sE2u12GI1G7N69G+3t7fB4PJQEsltw7JsShmFoQgqZbK+pqUnbLBvYOAdGRkbA4XDQ09OTdgWE\n6ASJRmkznSKb5BEdp8FggEqlglQqTSmhg61n27FjBwKBANbW1tDS0oLu7m4wDAOn00mr3MSaI7oS\nyP6sRH4gk8kS5p8Sb0WdToeysjIaJ0d+Njo6Cp/Ph76+vi2Xa0tSilQqFSQSCbq6uhKScrZnJSGB\nbrcbwKU3O04Vdrsd8/PzcX3+GIbBa6+9hkcffRT79u3DH/7wh4z0ppcCgUAAd9xxBz70oQ/hfe97\nX8zP2WvCu9/9bnzqU5+CyWRCVVUVFhcX6c+WlpYysvrZRmJsT+NeQZCFdzP4fD6cOnUKfr+fZomy\nCR6wcVItLS1hdXU1wu/M7/djYGAAfr8/qW1Eou07c+YMzGYzWltbaZWPtI7IQAObvLAvdGNjY1ha\nWkJHR0fSwGy2Ia9EIkFtbS2sVmvG068+nw8DAwMIhULo7+9PO1sznelVcnet0WggFApRXl6OiYkJ\nMAyD/v5+ehFmm8tGJ12wFwu73U7zRuNlnm6GzSxWouFwOKBWq+H1elFRUYHZ2Vk4HA5qzxFvujNR\nwoXH48HY2BiCwSCamppStlghxC8UCmF6eho8Hg+7d++Oma4mRIJY67jdbthsNoRCIeTm5qKgoADz\n8/MQCAS44YYbIJFI0p6aHhoagtVqxZ49e+KS/M0QHQGWCOyWZ1VVFaqqqsDj8WCxWOjwUSaT1yRC\ncH19PeFnSDbZmpWVhUAggPn5eVRUVODAgQMxJIhdDSsuLoZMJouRZpBzf9euXRll/15OkOzd7Oxs\nKBSKjA2R2VY77Bxr9pQ1Owv8UlQ23W43lEolgsEgGhoaIm4miEPDI488gpKSEnzta1+L0HRfaaSS\nfLG6uoqysjJwOBwMDQ3h/e9/P7RaLUKhEBobG/Haa6+hqqoKvb29+MUvfpH2UOBfKLatV7YakuXj\nEgSDQbz66qvUS4944JHqiMfjgU6ng8VioZUkclEJhUIYGhqCzWZLe/Eiep3V1dW4xIGdd0se7Kgz\ns9mMlZUVtLW1oaOjI+6iGwwGqQVJSUkJampqIBQKL8pqhB0n1dfXl7Yf1tLSUkpxWAzDwGg0QqvV\nIjc3FzKZDCKRCKdPn4bT6cS+ffvimjpHg6SYkMrL0NAQsrKy0NbWRi1NokXkiZAOSSWZu+FwGHK5\nHBKJBKOjozAajeju7kZpaemm285GKBTC4OAg7HY7+vr6IBaLNyWJ7K99Ph+tiLW2tiIrKyuivc22\nCPH7/TAajXC5XCgtLaWWElNTU7BYLNTKhmEYCAQCug/ZE9bxvCBnZ2dhMBiwc+dO1NTURKTNpAIS\ng5fs2AmFQtSfsLKyElKplJ6vbD/A/fv3Z2QfQkyP0zErJyDyiTfeeAOhUAjNzc20AiwUCpGbmwuG\nYbC+vo6ioiLU1dXF3UYSx1ZXV5dRSsflgsPhgFKpBJfLRV1d3WUzRGZPWbOzwKO1lem01f1+P1Qq\nFbWAiW6rq9VqHDt2DBaLBY8//nhGVe1LjZMnT+LAgQPo6Oig51B08sUPf/hD/PjHPwafz0d2dja+\n+93vor+/HwBw/PhxfPazn0UoFMLHPvYxPPzww1fts1xj2CZ7Ww2JyB576CIUCuGFF15AMBhEYWEh\nfY7b7cba2hpCoRDKy8uxY8cOSgLJIqXRaGA0GtHe3o7Kysq44n72g31xmJqagkaj2bRCEe8zKZVK\nDA8PQywWo7q6OiLqjExhWq1WrK+v06oGueCxDXRT1Tux99vo6CgMBgO6urrStngwmUwYHh6mMULx\nFnl2FbKwsBC1tbUQiUT0vY1GI7q6uiKiy1KBy+XCqVOnaLoGl8uNqAKSsPTogQYyXEOIRlVVVdKK\nIGk1c7lcyOVySkjJ37u1tTXtljmpKKRTUYx+Pbmx6O7ujrvvGIaBy+XCwsICvbEpLCykrenJyUks\nLS2hoaEBxcXFlCRGJ12Q4RpiFk3anzabDaurq6ioqIhpF0UbFEe3rknFe3JyEoWFhbQlyH4+ABiN\nRqrJq66ujqj0hEIhDAwMZOxHCGxM3k5OTkIul2c0VMI2j2Z7GpKEF7VaDYFAgOzsbHi9XgQCAUoC\nCYHxer04f/48SktL0dXlQ3UoAAAgAElEQVTVddUJB7BxrSRWS3V1dSndhF0ORGsrySNR4oVAIKAD\nO0ajkUbKsfepyWTCt771LQwPD+Po0aO4+eabt8Q+38ZVxTbZ22ogTufs/8cbunC5XPQOm2jaAKC8\nvBzZ2dkJrUTcbjesVmvKFT2ycAWDQUxOTqKqqgr19fV0oWOTyURToTabDefPn0dRUVHE6H8oFKID\nI06nk7b42CkXQqEQ4+PjtAWarpj4YgiLw+HA6dOnIRKJsG/fvpi2VCgUgl6vh16vj6hCXor3Jq32\nQCCw6ecmAw1s8mIymTA3N4fS0lJaVcvLy6OfgVRjNBoNBAIB5HJ5BJkgJKG2tjajNglpXTY1NWXU\nNpqZmYFKpUp4Y+HxeKDRaOBwOCCTyWISZ0iySToxcoFAADabDXa7HWq1GmfPnkVubi4aGhqQnZ0N\noVAIkUhEfdnYFcZ459n4+Di4XC6am5sjjp1wOAyz2Qyz2YzCwkLs2LEjrhHxwsIC7HY72traUFJS\nkvJADfnabDZjeHgYJSUlGVV1GIbB2bNnsba2RtN4ANA8YBJBGC2JYHvcmUwmDAwMgMvloquri6Z9\nEPJypTNWvV4v1Go1nE4nFArFRZsEXy6wEy/YCTYkgi8/Px9lZWXweDzIz89HZWUlXC4XfvSjH+FX\nv/oV/t//+3/48Ic/vGUGYLZx1bFN9rYayEnOJnjRSRfAxoKxurqKxcVFmgebDhFK5kMX7/vBYBB2\nux1CoTDmOZs57hsMBphMJjQ3NyMrK4smX5AqZHV1NV3wSMXD7/fD4/FgdHSUuvyXlJRALBZDLBZD\nIpEgPz8/6cVMrVZjenoaMpksbS8mookMh8PYv39/hIaHrYWsqKiAVCqNabuQtlUm781O18hEJ0Yq\ngjweDx0dHRFDNqRq7Pf7kZ2djZqaGrrvCdbW1jAyMpIxSUildZkMpG1eXV1NDXsJPB4PXazjkTxg\nQ/MzOjqakbYT2BC6DwwMID8/H319fQiHwxHVVLIfSTuYXVUllRdSDevr66M3X36/H4uLi1hcXERx\ncXHc3F3y78LCAnQ6HaRSKUpLS1M+1wi8Xi9mZ2chEonQ2dmJrKysTf0fo78m29DR0YG6ujrY7XYs\nLCyAz+ejrq5u0+tNIBDAqVOnEAgEsH///gh9L9mXgUAg7oDNpSaBxOfPbDZDoVBkHEd5NUDkIWq1\nmlpkEX3lb37zGzz//PMwmUxwOp1oaGjAnXfeiZ07d1Lv0Yv9nKmkXvz85z/HN7/5TTAMg/z8fPz4\nxz+m3QSZTEav1Xw+HyMjIxe1PdvICNtkb6thfX0dZrMZZWVl4HK5MUMX0Zq26urqtHNFLzWiUy/i\nTXr6/X6EQiGsr69jcXER4XAYJSUlEZOh5DXkeGMYBnq9Hrm5uZBIJFTwT4yN/X5/hAUCW4fl8Xgw\nMTGB0tJS7Ny5M0LTGK9dzW7PsjV+bJ2dz+eDTqeDyWRKmp9qMBgwOjqacdsq3YEKNhJVBNl6wuzs\nbDqhSRZe0jbicDiYmZlBYWEhbrjhhrSPLVJNIjnF6Q4TkNcXFRVFtM3ZJE8ul2PHjh1x96vNZsPp\n06cpUUu3skFIPsMw2L9/f9KJ0XiVF7/fj4WFBXg8HvT19aG6uho5OTlYW1vD4uIiSktLUVNTk9RX\nMhlZjhdVGF1h9Hg8GBkZgdfrRUdHB820jndTl8iyx2w2U3JRWlqKlZUVcLlcSKVS5Ofnb1ph5PF4\nUKlU8Pv92LNnT9IKGvs4ZO9HUuGPrgSmcz6FQiHqUVhbW3tJyM+VxPr6OhYWFpCXlweFQhFxPobD\nYbz88sv4xje+gUOHDuGTn/wkjEYjpqam6OPAgQP44he/eFHbsLKygpWVlYjUixdffDHiJnZgYAAt\nLS0oLCzEyy+/jKNHj1IPPJlMhpGREVoZ3sZVwTbZ22oYHBzEV7/6VaysrEAsFtNcwpKSErz88stw\nuVz4xje+QfV21wLYRCMnJwcymSypEDpRdTHR910uFw2YJ5WDQCAAu92O8vJy5OTkQCQSJR1mIEbI\nfD4fZrMZS0tLaGlpoVUVkqAhlUpRXl4eo78iD5fLheHhYeTl5WHfvn1pk42LyayNVxEk2iqtVguJ\nREKHRqLBMAzsdjveeOMNeDweNDY2IhQKRQjIySPRFGG0xjDdQPp4r3e73VCr1XC73ZDJZAlJHrBR\nzTp16hQ4HA7279+fNlFlD5SkOkwTjampKczPz0Mmk6GwsJBGgxFdZX5+fowGiw0yeSuRSDJKamAY\nBsPDw0knb6OfH13lJzpVoVBIb8YqKytjLHsSfc0wDBYXF8HhcPCud70r6dR9MkSTQKJRTVQJZB8X\nbJ+/qqoqSKXSq+6Blw7YgyP19fURVVSGYTA0NISjR49CJpPh0UcfzSjNJVPcdttt+PSnP43Dhw/H\n/TmJgdTr9QC2yd4WwTbZ26pgGAYWiwUvvfQSnn76aeh0OjQ3N8NsNqO8vJySwPb2djQ3N8cNnL/a\nCIfDWF5extLSEgoLC1FTU5OxpUEm7+3xeGC326kOy+l0UvJCyF9WVha4XG7MgmW1WsEwDJaWluB2\nu7Fjxw5qb5MMRHDf1taGnJycuBOe8SqLPB4PRqMRMzMzqKmpodXIdCY/z58/j+XlZezatQvl5eV0\naKSoqAi1tbVJyU+iamZ0QgN7ipBYSZABm/Pnz1PT4HS1ldEtP4ZhoFar4fF4IJfLUVxcnHTfs7e/\nv79/U//GeCAV1UwGeYCNdtf4+DhqampQVFQEnU6HHTt2oLa2FgKBIKKdzq6oEuNyHo+HyclJ5Obm\n4uDBgxm1MicnJ6HVaje1NkoEj8eD119/HWtra2hubkZjY2PaMgKtVovz589DJpNlZBW0GdgaVfIv\nmwSGQiHYbDaUlJRAoVCkfdNxNeHxeKBSqah5evQNx+zsLI4dO4ZAIIDHHnvssuzfZNBoNDh48CAm\nJiYSnmNPPPEEZmZm8MwzzwAAHfri8Xi4//77cd99913JTd7GBrbJ3lbG0aNHMTw8jAcffBDXX389\nOBwOJVDj4+MYGxvDxMQEZmdn4fP5IJfL0draira2NrS2tqKuru6qVP8S+fttBbBtTdiTmOyJVg6H\nA5PJhHA4DJlMhqKiogiD6s2qjl6vFwCSViNJ1YwNm82GtbU1KBSKCIJHJj8TkUQ+n0+jkcighdFo\nRGlpKWprayNIZ7yKHHvyNVWiw7bZcTgcGBwcpKa95eXlEVWXzZIF2F527e3tsFqt8Hq9kMvlEfs+\n2bZsNrm7Gebn5zE/P5/xQInZbKZtKzJ0UVtbu+lxTzS6NpsNf/zjH2G1WtHQ0AChUEinMdn7Mtn5\nrNPpMDExkZFOFNgwHX/xxRdhsVhw6623oqamJu0bSGKRVFRUhN7e3it2A8owDDWeFolEdDrY5/NF\nTP2nmsF8pREIBKBWq2GxWKBQKGIq2Kurq3j88ccxOTmJr3/963Q9uJJwOp247rrr8PDDD8c1QwaA\nN954A5/61Kdw8uRJ2rrX6/WoqqqC0WjE4cOH8dRTT+HgwYNXctO3sU32tjZ8Pl/KrahgMAilUkkJ\n4MTEBFQqFfh8PhobGykBbG9vTzv8PZ3tJZo2tinstYBAIEAHXsLhMPVkY08GJ2q9ZQpioxMIBOJq\nqQKBQEKtVbzpz/n5efD5fEgkkpihCwIOh0Pb1eRhs9mgVCqhUCggk8lSrkYSax5ilrtz505UVFRE\neC0SU9lobSWJlyKvn5+fh0QiQUFBQcokjyBV0+JEWF5exvnz5ze1qEkEp9OJ3/72t7BYLDh48CAl\na6mCbdHT09ODkpISSgLZ1atkSRdWqxXDw8PYsWMHenp60jYcV6vVGBwchFAoxKFDhzIizG63G6dO\nnYJAIMD+/fuvWEWN6Npyc3OhUChiZArsDGZ2JZCQQPZ+vNIdEraRdjxNocPhwPe//30cP34cDz30\nEO66666r0o4OBAJ473vfi5tuugmf+9zn4j5nbGwMt99+O15++eWEE/BHjx5FXl4eHnzwwcu5uduI\nxTbZ+3MGqb5MT09HkMBoPWBbWxva2trSThcgcLlc0Gq1cDgcqKmpocMl1wJIRJJGo0F2dnaMnpAt\nwicP9oLLJi9Xg9gGg0G6WJSWltKqXDKCGO//JpMJeXl5CauOyd5/ZmYGlZWVqK2tBZ/Pp+3naNF+\nIBCg1Rafzwe/308Jdk1NDfr7+1FeXp7Wgnuxk78Xk05B2vy/+93vkJWVhdtuuy2jhA1iM5OKRQ87\n6YJtb3Lu3DmqE5VIJCmZ87InVIPBIGw2G1pbWzMizMFgEKdPn4bH40k7lSdT2O12KJXKlKeDoxEK\nhWKmg4n/Jzv3Ni8v75KTQIZhsLy8DJ1Oh4qKihiPRb/fj5/+9Kd49tln8fd///f4xCc+cdW6I6mk\nXuh0Ohw6dAj/8R//QQ2QAdBkpfz8fLhcLhw+fBhHjhzB3XffDQB0qn0blx3bZO8vEUQPOD4+jvHx\ncUxMTGBychJWqxUVFRUp6wFtNhs0Gg0CgQBkMtmmuqqtBDK4oNPpIBaLIZPJUtYTRi+4ZKGI1rGR\nYYbLQXwDgQA1Vk02GZwp0rHmcblc4PF4CauO8Yijx+PB6uoq9Ho9HdohBJBUVtlkWiwWQyQSRfg6\nOp1OjI2N0clfYutDSOZmx2Km6RRsK4zFxUWIRCL09/dn5NlGbGZqamrQ3t6e9usDgQCNPmRn3pJj\nMhQKQSQSRSQ0iEQi6PV6GAwG1NTUgGGYlBJiEiFeZfJyghhpB4NB1NfXZ6TPTIZQKERzb8k57vV6\naYwhuxKYKMs6Edj5u0VFRTGxcuFwGC+99BKeeOIJvOc978HnP//5q2b4TJBK6sW9996L//3f/0Vt\nbS0AUIsVlUqF22+/HcDGDUFrayt+97vfUW0ysLFP3nzzTVRWVqbsibmNtLFN9rbxNlLRA7a2tsJk\nMuG5557Dpz71Kdx8881px49dTbCHRlIZXEgHbB0bu1oAIEYzlO4iQeD3+6HVamE2mynJ2+pVVIZh\nKBG0Wq1QKpXw+/2oqqpCXl5e3HY1SRVgPzweDwDQhAsejweTyQSFQhG3ghXdro5uS4+Pj8Pv96O3\ntxdisXhTax6GYbC2tgaNRgOxWAy3243V1dWMhyGIvi1Tmxr25G1vb29csslOaHA4HDAajXA6nRAI\nBMjPz0c4HMbMzAzKyspw3XXXZVRludg2eqrwer1QqVRwuVyoq6vLqIp6MYgmgS6XKyLLmk0E453f\n5NjPzs5GXV1dRLuZYRicPHkSx44dQ0dHBx555JEtlx98KTAxMYFDhw7hb//2b/Gtb30Lzz33HD77\n2c9S79XHH38c99xzzyUn8NvYJnvbSAGkVffMM8/ghRdeQEFBAcRiMQKBwBXTA14s2P6EZWVlNCv1\nSiAcDtNFgiwUHo8nQji+Wdat1+uFVquFxWJBbW3tNdUqBza0RyqVCqFQCAqFIuMbBGKpQyas7XY7\nrbqwp6xJlY4QyXhVR4vFgmAwuGnlhGEYOBwO2uqWSqVgGAaTk5Oorq5GfX19UlIZ7/ukqngx+rZU\nJ2/D4TCWlpag1+tpy5DL5cJqteLEiRPw+Xxobm6mXpikEsiuBiaqGhO9Y6ZVwVTg9/uh0WhgsVgg\nl8u3nCEyGfpit4QJCczJyYFQKITNZgOXy0VTU1NM7N3U1BQeeeQRCIVCPPbYYxnF2m1VWK1W6pHK\n5/MRCATw7W9/G9/4xjcwMDCAY8eOobe3Fz09PXjmmWfw5ptv4ktf+hIeeOCBq73pf27YJnvb2Bxu\ntxsHDhzADTfcgM9+9rN0sbsSesCLBUktMBqNMSHzVxtEMxRtIcHj8SISGdbW1qjPXGlp6ZZa6DaD\n3W6HSqUCwzBQKBSXrSUVra0kXovsiVZCXthVwESG4ORBKnlZWVkoLy+n7WpiEM6OJmQbgm+GtbU1\nGAwGdHR00KoiqSCSr4n2MR55XFlZoXFwieLsSGazTqdDWVkZampq6GcPhUI4ffo0XC4X9u3bRysp\nyax22O3gvLw8+P1+DA8PZ6R3TAXB4NsZsDU1NdecIbLH48H8/DwcDgckEgmtDD7zzDMwmUyQyWRQ\nqVSw2Wz49re/jeuuu+6a+nyb4eWXX8b//d//4ctf/jLNliZRgX19fXA4HLjhhhvwb//2b1TjeeON\nN8Lv9+Of//mfM5oo30ZCbJO9baQGt9sdk4EZD5dKD3ix8Hq90Ol0WF9fv2banQSBQIBmBns8Hlql\nIn5siYjLVoLNZoNKpQKAy0rykiE6X5Q90RpNXNjVK4ZhaIJETk4OFApFynrOdAzBXS4X+Hx+ytY8\nbOj1erjd7oicajYpJDY+xcXFqK6uhkgkiqguTk5Owmw2o7u7m+o92XGF8fYlmwSazWacOXMGALBn\nzx4UFhZG7MuLOdfYlchr0RA5GAxCo9HAZDJBLpfH3KAZDAZ861vfwsTEBKRSKcLhMBYWFsAwDOrr\n6/GJT3wCN9xww0VvRyoxZwzD4MiRIzh+/DhycnLws5/9DF1dXQCAV155BUeOHEEoFMK9996Lhx56\naNP3PHPmDPr6+gAAo6Oj6OnpwbPPPovdu3fjrrvuwrvf/W48+eSTePbZZ3Hvvffii1/8Ir7+9a/T\nSNAXXngBDz/8MO644w489thjF70PtkGxTfa2cWVwpfwB3W43NBoNHA4HbXdeS3fLDocDarUafr8/\nxoKEbcobj7iwSeDVWhwJyeNwOFAoFFtSe8PWsbErq6FQCDweD16vl05mFxcXX7V9Sax5EpHBeFpH\nEsuWnZ2N0tJSAG/7PbJhMBjAMExcT8XNPB15PB7UajW4XC727dsHgUAQk3TBMEzEsBJpByfblwzD\nYGVlBVqtNqYSeS2ATVKrq6tjbjC9Xi/+9V//Fc899xw+/elP42Mf+1hE+z4YDGJhYQE5OTkZp46w\nkUrM2fHjx/HUU0/h+PHjGBwcxJEjRzA4OIhQKITGxka8+uqrkEql6O3txfPPP5+02vbmm2/ihhtu\nwP/8z//gjjvuAAB86EMfwvHjx+FwOPDe974XX/7yl9HT04PV1VXcfvvtyMnJwcsvvwyBQECvc3ff\nfTfUajV+8IMfUOK4jYvGNtnbxtXFpfIHdDgc0Gg08Hq9m8ZqbUWQdmc4HIZcLkdhYWFKr2MTFzYJ\nJIstmwRuZm58MbBarVCpVODxeFAoFDG6pK0O4tUmEAhQXFxMK2/x9mVubu5lm7LOBKQSqVKpkJ+f\nD7lcHuM1xx6SiTctncjrMRHRJNF7iQy44w0rud3uiH3JHmYgldR4E6pbHcTQWaPRUCNztlQkFArh\nv//7v/GDH/wA73//+/G5z30ubZuYS4F4MWf3338/rr/+etxzzz0AgKamJpw4cQIajQZHjx7F73//\newDA448/DgBJc3aNRiM+/vGPY3V1FWfOnIHBYIBCoYDf78ff/M3f4Mc//nFEd+iXv/wl7rnnHrzy\nyiu48cYbEQ6HweVy8dprr+Ef//Ef0d/fj6effvpy7Iq/RKS0GF47t1bbuObA5/PR3NyM5uZm3HXX\nXQBi/QFPnjyJp59+Oq4e0GKx4Ic//CEeeOABHDhwIGWStFVgtVqhVqsBZNbu5HA4dDqVnT3JMAzc\nbjddaA0GAzU3Zk8NXqyHmMVigVqtBo/HQ0NDwzVH8iwWC1QqFYRCIVpbW+Muwon2JYAYo+icnJwr\nepNBSGpOTg46OjoStps5HE7SNm26IG23RCDDCdHSj2gSqNfr6fBCQUEBuFwu1tfXtxyhTgSz2YyF\nhQWIxWJ0dXVF2PcwDIPXX38djz76KPbu3YtXX32VVluvNDQaDc6dO4e9e/dGfJ9UIQmkUin0en3c\n75OEmGgQr7zS0lJ85jOfwa233oqf/exn+PjHP47h4WH8+7//O372s59Bq9VGDJ/cdNNNOHToEI4d\nO4brrruOuiK8853vRGNjI7VuUSgUl3JXbCMJtsneJUAoFEJPTw+qqqrw29/+NuJnl1o3ca2DLBTd\n3d3o7u6m3yd6wLGxMbzwwgt44oknkJ2djR07duDZZ5/FmTNntnxeMPD251Cr1RAIBKivr7/kJIlN\n6tgLDDsuzmazQa/XUyNZNmmJFy7PBiFJAoEAjY2NV8RE91LCarXSSl5TU1PS7U+2LwkJdDgcWFlZ\nibHiuBSEerPtT0RSLycy/Szk3CaRikKhEH19fRCJRPB4PPTYNBqNtBKYk5MT0Q7eCiSQGDoLBAK0\nt7dHkFqGYXDhwgUcPXoURUVF+MUvfoH6+vqrtq1OpxN33HEHvve9710WWQWpwr766qvwer14xzve\ngSeffBJ33XUXOjo68OCDD+IXv/gFfvSjH+E73/kOJXUSiQRf+MIX8O53vxsvvvgi7r77biqlePLJ\nJyGRSK65m8drHdtk7xLg+9//PlpaWmC322N+9vLLL9NszsHBQXzyk5+kuokHHnggQjdx6623/sVO\nKXE4HAgEAjz88MNoamrC66+/jqamphg94NNPP43Z2Vn4/X6aE3q184KB2LSOzUjG5QCXy0V+fn7M\nRZRESjmdTpjNZmi1Wvj9/oi4uNzcXAQCASwuLqZEkrYi2O3mi91+NkFmx4slI9QXm9HqcDigVCrB\n4XDQ2Nh4zS2GLpcLSqUS4XA4phKciFCzK4HRVVU2ob6cMgUCj8cDpVKJQCAQ19BZo9Hgn/7pn2Ay\nmfD444+nHV13qREIBHDHHXfgQx/6UNw826qqKiwuLtL/Ly0toaqqip7n7O/Pz8/jRz/6Ee6///6I\na+js7CzuvvtumEwm7N69G/Pz89DpdHj22Wdx5MgRlJeX4wtf+AK+9KUv4cMf/nCEDm///v14//vf\njyNHjuCmm26ilkyXQrO4jfSxTfYuEiRS6eGHH8Z3v/vdmJ+/9NJL+MhHPgIOh4O+vj5YrVasrKxA\no9Ggvr6elrE/8IEP4KWXXvqLJXsAkJ+fj1/96lcRiyuXy4VUKoVUKsW73vUu+n2iBySTwb/61a/o\nQn8l/QHZZrz/v70zj4uqbt//NQzDyCq74qCssouKolaKS6mJhmJaiD1qipq5lFuLkqKiFpiaoqhl\nmqaR8UhKgtljkGIJphnuwgDDviogA8z6+f3Bd85vhhkQdFj9vF8vX9mcmeOZA3PmOp/7vq/LyMgI\nnp6eLZpsbk/YbDZ69uypVkaWSCRM6VLRU6hopi4sLFQRLp3F0kYTisERHR2dNi83NyeoFSLw8ePH\nyMvLY6x2GovAxquqNTU1yMrKglQqhZOTU4enKrSWuro6ZGVloa6uDk5OTi1ut1DOr1VGWQQ+rbSu\nDREoFouRnZ2NqqoqODk5qRlYl5eXIzIyEqmpqQgLC8OkSZM6vKpACMGCBQvg7u7eZJ5tQEAAoqKi\nEBQUxMQG2tjYwMrKChkZGcjOzgaPx0NMTAzs7OxgZGSkdrN86NAhiMVinD17Fg4ODnjw4AHWrFmD\nrVu3YtasWbC2tsa8efNw8OBBREVFwcvLC0ZGRigtLYW1tTWWL1+OiooKiMXi9jgtlGagYu85+fDD\nDxEREYEnT55o3K6NvokXiZaGtCv3A86cOROAaj/grVu3mu0HfF5/QEIIiouLkZubi549ezbbU9UZ\nIYQwgyP6+voYMmQIDA0NGUsTxRdtfn4+M83aeCiko0tu1dXV4PP5YLFYcHJy6tDpYDabDRMTE7Vj\nUAyD1NTUoLy8HAKBACKRCBwOB1wul/G5c3Z2bvMoMm2jEEmVlZVwdHTU2uCUsghsvKqqXFovLi5m\nelU1lYOfdiwymQy5ubkoKSmBnZ0dXFxcVF5TW1uL/fv3IzY2FqtWrcLu3bs7zU3PlStXcPz4cQwY\nMACDBg0CoB5z5u/vj4SEBDg7O8PAwABHjhwB0HDtjIqKwsSJEyGTyTB//nysW7cOLBYLNTU14HK5\n4HA4qKmpwbVr1+Du7s60Ho0YMQKRkZGYOnUqIiIisGPHDpiammLDhg2YPXs2LCws0KtXL4SGhiI2\nNhbTp0/Hb7/91jEniaICFXvPwS+//AJra2sMGTIEycnJHX04LzxP6wdUXgXcsmXLM/kDKsxs8/Ly\nYG5ujkGDBmktkq09aOwz17gnTJFWweVyVVY4lL3YampqGDNoRd9V48ngtlz5ePLkCeNd1lE+fy1F\nV1dXbVW1vr4emZmZqK6uZmLBBAIBMjMzGb9FZeHS2aZXpVIpBAIBysrKNIqktqK50roixaZxf6Xi\nd1N5OpgQgsLCQuTl5YHH42HYsGEqNy1SqRQnTpxAdHQ03nnnHaSmpna6G7mRI0c+1eSbxWJh3759\nGrf5+/urrVD+9NNPWLFiBWJiYpihirKyMgwaNAgymQw6OjpgsVjw9vbGnDlzcODAASxZsgROTk6Y\nNWsW/vzzT6SkpKC6uhpffPGFxtIypeOgYu85uHLlCs6ePYuEhATU19ejuroa77zzDr7//nvmOa3p\nm1A4kVO0C4vFgrm5OUaPHo3Ro0czj7emH7B37944dOgQRCIRgoKC1KbzOjvKPYUGBgatLjezWCzo\n6+tDX19fZQVKueSmaZBBWQS2toetMcqxbF2x3CkSiZCTk4PKyko4ODjA09NT7XwoVlWFQiGKiopQ\nU1MDqVQKLperNmTT3qtMMpkM+fn5KCwshK2trZpI6iiURaAyyiKwuroahYWFTJKNslfh/fv34erq\nChaLhfPnz2P79u0YO3YskpOT2z2jtz1R/O7FxsZixowZeO2111BSUoL4+HgMGDAA5ubmGDt2LC5c\nuICqqirmXBgaGsLFxYVZ+fzyyy8BALt27UJJSQn9HuukUJ89LZGcnIwdO3aoTeOeO3cOUVFRjLHl\nihUrkJaWBqlUChcXF1y8eBE8Hg++vr44efJkk/FILaG5qeATJ07giy++ACEExsbGiI6OxsCBAwEA\n9vb2MDY2ZoxV//7772c+hu6Acj/gjRs3kJCQAIFAAA8PD9jZ2cHLy6vT5wUrUIi87OxsGBkZwcHB\noV1WKZSD5RV/6qlhs9oAACAASURBVOvroaurqyYCnyaalXvanid7t6OQSCTIyclBRUUF7O3tW20G\n3ri0rigLN866VZTWtS0ClaPZevfujX79+nWacmZLqaysREZGBgwNDWFvb8/0WN67dw8RERHIz89H\nfX09evTogZkzZ2LkyJHw9PSEnZ2d1j7f8+fPZ6pBt2/fVtseGRmJEydOAGi4Bt27dw9lZWWMP+Hz\nXqMV07DKHD9+HIsXL0ZKSgp8fHwQGhqKqKgoxMbG4rXXXsONGzfw8ssvY+vWrVi+fDnzWY2MjMT2\n7dtRWVmJtLQ0DB069BnOCEVLUJ+9jkJhFtnavonnEXpA81PBDg4O+OOPP2BmZobExEQsWrRIpUcw\nKSlJxcvtRUbRD/jHH38gISEB//nPf7B48WKw2ex26QfUBo0HR9q7p5DNZmscZJBKpSqlYEWiSOPy\npZGREUQiEfh8PiQSCRwdHbucz6Ki3FlaWgo7Ozs4OTk9k3B4WmldIf4qKiqYHkDlhItn7a8khKC0\ntBTZ2dmwsLDA0KFDO11J+WnU1NQwE86NWxaMjY2ZUrqhoSE2btwILpeLu3fv4urVqzh8+DBKS0uR\nkpKilc/yvHnzsGzZMsyZM0fj9rVr12Lt2rUAgPj4eOzatUtlZfF5r9EKocfn89GrVy8YGRnBwsIC\nrq6uyMrKgo+PD8LDw7F//34cP34cPj4+8PHxwerVq7FhwwaIxWJMmzYNlZWVuHjxIiIjI5kbGErn\nh67sdRPy8/Mxd+5cZiq48cqeMo8fP4aXlxcKCgoANKzs/f3331TsNeLGjRtwd3dvViR1lrxg5eMp\nLS2FQCCAsbEx7O3tO12/kSaUV64qKyvx6NEjyOVyGBkZwczMrE1XrrSNTCZDXl4eioqKYGtrCx6P\n166rv4pBJeXcYE2+dk1ZmhBCGENnExMTODg4dKm+VKChL5LP56Ourg7Ozs5qq8HFxcX4/PPPcfv2\nbYSHh2Ps2LHtcnOWk5ODKVOmaFzZUyY4OBhjx47FwoULATzbNVoul4PFYqlEMq5duxYHDx7El19+\niaVLlwJosEJZvHgxQkNDAQD79u3DqlWrcOrUKUydOhUAEBISgri4OHC5XJSXl8Pf3x+HDh3qMCNp\nigo0Lu1FYsaMGfj000/x5MkTjeVkZXbs2IH79+/jm2++AdCw6tezZ0+w2WwsXrwYixYtaq/D7rY0\nlRfcVv6ACpGXk5ODnj17wt7eXi1Wq7NTW1uLrKws1NfXM+XaxuVLoVDIrFx1togz5fzUPn36wNbW\ntlMJ08a+dgoRqDzIwGKxUFpaCn19fTg5OXU6G6GnoSiZP3r0SOOE8JMnT7Bnzx6cO3cOH3/8Md5+\n++12/b1pidirra2Fra0tMjMzmZW957lGK1IwRCIRPvroIxw7dgyWlpYIDw/H22+/jeXLlyM5ORm3\nbt1iXuPg4ABvb2/s2bMHdnZ2EAqFEAgEuHLlCvr3748xY8Y88zmgaB1axn1RaM1UcFJSEg4fPoyU\nlBTmsZSUFPB4PJSWlmL8+PFwc3ODn59fGx9196a9/AEV2Z0CgQCmpqYYOHBglxR52dnZqK2thaOj\nI8zNzZkv6Kbi4pryYWvcD9geSSsKYZ+Xl4fevXvD19e3w8y9m6M5X7vy8nJm+IXL5UIoFOL27dtq\n06ydNblGLpcjLy8PhYWF6Nevn1rJXCwW48iRI/j2228REhKCtLS0TjtgFR8fj1deeUWlhPus1+h1\n69ahrq4Oa9asAY/Hg5ubG+zt7REYGIiQkBC4uLhg9OjROHv2LFJTU5nItS+//BJBQUFITk7G3Llz\nYWhoCA8PjxfaB7arQ1f2ugGffvopjh8/Dl1dXWYqePr06SpTwQCQnp6OwMBAJCYmwsXFReO+wsLC\nYGRkhDVr1rTHoVOg7g+oKAcXFRXB2NiYucgqVgPNzMwgk8nw7bffws7ODvb29rC3t+9ypba6ujpk\nZ2dDKBTCwcEBFhYWzyUklKcvlYdClNMtlIdCnle0KLwWBQIBLC0tYWdn1+V62urq6sDn81FfX69W\n7tQ0ZCMSidTOp6Gh4XNPWj8rhBAUFRVBIBBoHB6Ry+U4c+YMduzYAX9/f3z00UcdOsXdkpW9wMBA\nzJw5E8HBwRq3K67R77zzDv773/8y5VhlFPnGmzZtQlxcHIYOHYpvvvkGjx49grW1Nfh8PrZu3Qqh\nUAhHR0dcvXoV06dPx5IlS5h99OvXDx4eHjh16lSHelhSngot476INDUVnJubi3HjxuHYsWN4+eWX\nmccVZTFjY2MIhUKMHz8eGzZswOuvv/5cx9HcZHBycjKmTp0KBwcHAMD06dOxYcMGAC9mXnBTaOoH\nvHXrFnJzcyGXy+Hm5oY33ngDvr6+cHV1bXN/O21RX1+PrKws1NTUwMHBQWtmvE2hnG6hLFqU4+IU\nf1oi1pRL5mZmZrC3t++0q0RNIRKJkJ2djerqajg6OrZKaCvi95TPqVgsVkkLaemk9bOi8Ivk8/ka\nfwaEEKSkpGDz5s3w8PDApk2b0KdPnzY5ltbwNLFXVVUFBwcH5OXlMSuwTV2jCwoKsHDhQvzxxx8Y\nNWqUyn7kcjl0dHQglUpx+PBhrFy5Ep9//jmWLl2K4OBguLq6Ys2aNdiwYQOuX7+OW7duYdWqVQgN\nDYVUKoWenh4EAgFsbGy63O/2Cwgt477oKE8Fb968GRUVFXj//fcBgBnfLykpQWBgIICGEmNwcPBz\nCz2g+clgABg1apSaCKR5waoo+wOOHDkSJ06cwLVr1zBr1izMmjULxcXFnTovuDH19fXIyclBdXU1\n7O3t4e7u3i7itKl0C4lEwgiWkpISZvKXy+WqiRY2m61iY2NiYtIlS+YSiQQCgQDl5eWwt7dn/OVa\nQ3Pxe4rzqTxpzeFw1Catn2cFtKqqCpmZmeByufD29lYbQLp79y42btwIDoeDr7/+utNcP2bNmoXk\n5GSUl5fD1tYWmzZtgkQiAdBwjQaAuLg4TJgwQaXU3tQ1ury8HN999x3Cw8Nx7tw5lc+5jo4OCCHQ\n1dXFggUL8PjxY2zcuBE9evSAh4cH8vPzoaOjg1WrVmHHjh24cuUKvv/+e2zYsIERd/369esSN4+U\nlkFX9iha52mTwU2tPv71118ICwvDr7/+CgDYvn07gIYy9YuOXC7H7t27MWfOnCYn8hr3A965c6dD\n8oIbo1hFUqxaWFlZddovEWVPu8YrVxKJBD169ACPx4OZmRkMDQ07fCikpShPCPft2xd9+vRpt2NX\nZDArn1OJRMLY7SgLweZuTGpra5GZmQmZTAZnZ2c1W5+CggJs3boV2dnZCA8Px8iRIzvt75m2+Pnn\nn/Hmm28iLi4OAQEBzT43ODgY5eXlqKmpAY/Hw549e2BjYwOhUIhhw4bBxsYGZ86caVHUHKVTQcu4\nlI7haZPBycnJmD59OmNLsWPHDnh6eiI2Nhbnz59npoSPHz+O1NRUREVFdcTb6BY8Sz+gti70yokR\n9vb2sLa27nJfIpWVleDz+eBwOLC1tVUpCQuFQo12Jp3py1J5eMTGxgZ9+/btFBPCClGtLKiFQiGk\nUil69OihtgooEAhQXV0NZ2dntVSLyspK7Ny5E7///jtCQ0Mxbdq0LiPCWwohBIQQZsVO8ftVXV2N\n4OBgFBcX49KlSxqnpxVmyjk5Odi7dy8OHToEoVCIq1evYtiwYQAazmFXMyunMNAyLqX9aclksI+P\nD3Jzc2FkZISEhARMmzYNGRkZ7XugLwgtzQuOi4vDli1bUFVVpeYP2Np+QLFYzNhf2Nvbt1t2qjap\nrq4Gn8+Hjo4OXFxcVFaRmoqLU54MVo6L64hJVsWUdk5ODiwtLTudIbKyUbSyeCOEQCQSQSgUoqqq\nCrm5uRAKhcwqYH5+Pn766ScMHDgQrq6uOHHiBI4fP46lS5di+/btneo9aguFWGOxWIxfoqLMa2Ji\ngjVr1mDChAn48ccf8e6776q9XiHu7e3tsWrVKpSUlODkyZP47bffGLFHhV73h67sUbRKSyeDlVEY\nhmZkZNAybgfzPP6ARUVFKCkpQX19Pezs7NC7d+8uJ/JqamrA5/OfO39XLperDYXU19eDzWarDYVo\nswFeMbiQlZXVZQ2R5XI5CgoKkJ+fz6z+s1gs1NfXo6CgAEePHsX169eZG0RfX18MGjQInp6ezM2J\ntlYvnxZx1l7DZlKpFJ988glSUlLA5XIxevRohISEoF+/fqiursayZcvw559/Ii0t7al5vjU1NTh9\n+nSTSR6ULgct41I6lqZ684qLi5l80LS0NMyYMQMCgQAymUzrecEKmpsObutMyu5Ac/2AdnZ2qKmp\nQUZGBrZs2YI33nij0wyFtBSFobNIJGrTaDapVKomApWHGJR72Fq7SlVZWYnMzEz06NEDTk5OXSI5\nRRnleDYrKyvY2dmp/B4RQpCUlIQtW7bA19cXGzZsgIWFBbKzs3Hnzh0mvWb//v1aW6m6dOkSjIyM\nMGfOnCbFnqZrnOJapjxs9sMPPzQ5LCKRSFBfXw9jY2OIRCIVgX7+/HmsWrUKurq6CAkJQUlJCVJS\nUmBoaIiEhAQAwPXr1zFmzBh89tln+Oijj5p8P8olYEq3gZZxKZ0H5cng2NhYREdHQ1dXF/r6+oiJ\niQGLxWqTvGAFzU0Ht3UmZXdAkRfs5uaGmTNnAgAePXqEiIgIxMXFYdSoUfDw8MCxY8fwxRdftHk/\noLZQ9vprbOjcFujq6mqcZFXuXysqKkJNTQ2kUim4XK6aCGy8avXkyRPw+XwAgJubG4yMjNrs+NsK\nRTybsbExBg8erCJ2CCFIT09HWFgYTE1N8f3336N///7MdmdnZzg7OzPRXtrEz88POTk5rX5dWloa\nnJ2d4ejoCAAICgrCmTNnNIo9sViMH3/8ERcvXsTRo0eZ9y4UCmFoaIgrV67Az88PERERMDExwbVr\n1/DTTz8hMzMTp0+fxvTp0+Hh4YGFCxdix44dCA4Ohq2trcbj6myfP0r7QVf2KN2e1uQGayOT8kXh\nP//5D8aMGYM5c+aorEJp8ge8ffu2VvoBtYXyhLCmWK3OgHL/mvIQgyIuTk9PDzU1NSCEaBxc6Ao8\nefIEmZmZYLPZcHJyUkv3EAgE2Lx5M0pLS7F9+3b4+vq2+8+pOW88bQybEUIQExOD2bNn49dff4WR\nkREWLlyI2bNn49NPP8WlS5fg4uICDoeDRYsW4eeff8Zbb72F4uJi5ObmMkL//v37eO211xAcHIyI\niIi2PSmUzgRd2aNQAODDDz9EREQEnjx50uzzamtrcf78eZULMovFwmuvvUZzgzVw/PhxjY8r+wOO\nHj2aebxxP2BH+AOKxWIIBAJUVFQ8s89ce8FisZi4OAsLC+bx+vp6ZGRk4NGjRzA1NYVcLkdGRgYz\nGay8EthZjbYVyR0ikQjOzs5qK50VFRWIjIzE1atXsXHjRkyaNKlTTthqY9iMxWIhICAAI0eOxPTp\n0yEWi7F48WImQcPPzw9SqRRBQUEoKSnBhQsXMHr0aHz//feYP38+vv76ayxcuBAODg549913sXXr\nVixbtgz9+vVri7dM6aJQsUfp1rQmN1ibmZQUdVqbF6yrq4v+/ftrxR9QIpEgNzcXZWVlGrNTuwIS\niQQ5OTmoqKiAg4MDvLy8VIScIi5OKBTiyZMnKCoqQl1dnUomrkIEdlS8mUQiQXZ2Nh4/fgwnJye1\n5I7a2lpER0fjp59+wsqVK7Fr165OYRXTFMpG3f7+/nj//fdRXl4OHo+HvLw8Zlt+fj54PB6AhpU8\nuVwONpvNTNpev34dd+7cgVAoxCeffIJt27ZBKpUyr7927RouXLiAr776Cq+++ioAMCXhbdu2Yc6c\nOeByuViyZAleffVVKvQoalCxR+nyVFZWIiUlBXp6evDy8lKJRbpy5QrOnj2LhIQEZjr4nXfe0Tgd\nHBMTg1mzZqk8prhAW1tbIzAwEGlpaVTsaRlN/YCN/QFTUlJw8OBBFBYWtqofUCaTITc3F8XFxejb\nty+GDRvW5USe8ntoTqjq6OgwYq5Xr14qr1eUgh8/foy8vDzU19erxMUphGBbRWMpvwc7Ozv0799f\n5ecllUpx8uRJ7N+/H7Nnz0ZqamqXGDBpPGwml8thYWEBU1NTZGRkIDs7GzweDzExMTh58iQj7ths\nNiQSCSP6fHx8EB8fj+joaBw4cADbtm2Drq4u8/yCggIYGhrC3t4eQMP5+t///ofhw4cjNTUVkZGR\nCA0NRZ8+fTpFLByl80F79ihdnps3b+LNN99EdnY2M/QxduxYfPLJJxgxYgTzvKYm54DWZVJqI06O\n8mwQQlBZWcnYwigmgysrK1X6AZ2dnXHhwgXcuHEDe/bsga2tbadeIdKEsgVJnz59tP4elOPNFP2A\nYrFYJdlCIQSftaROCEFhYSFyc3M1mjrL5XL8+uuv2L59O0aPHo1169aplKw7GuWIs169eqlFnEVF\nRakMm+3cuZPJHk9ISMCHH37IDJutX7+e2W9YWBh+/vlnWFtbY/jw4Vi3bh309fWRlJSEadOmYfny\n5QgPD2d+HhKJBLa2thg+fDjeeecd6OvrIyIiAgsWLMCAAQNUPDQpLxzUeoXyYvD7779j3rx5WLdu\nHWbMmIHLly8jMjISUqkUJ06cYCb3lMWe8nQwABw9ehTnz59HTEwMs9+srCy1TErlC/az8jQ7F0II\nPvjgAyQkJMDAwABHjx6Fj48PAO16d3UnFP2A//zzD44cOYLk5GS4urpCLBajb9++nTYvWBOEEBQX\nF0MgEGi0IGlrFHFxmpItlEWggYFBk+JTkSOclZXFWBg1HuL5+++/ERYWBltbW4SHh8POzq693mKb\nIhaLER8fD0dHR/Tr148Rr4rBpeDgYDx8+BCLFi3CrVu3kJSUBF9fXxw9ehQGBgb46KOPcODAAZSW\nlqJnz56M4Dt58iTCw8NRXFwMsViM+fPnY8eOHW22GkvpMlCxR3kxOHbsGJYtW4YrV65gwIABABr8\nscaOHYuDBw8iJCSE8ZeSy+XM3xuXwsRiMSoqKmBpadmmTvxPm/BNSEjA3r17kZCQgNTUVHzwwQdI\nTU1ttXfXi0Z6ejrmzp2LgIAArFy5Eqampk36A2qzH1BbKAskU1NTODg4dJovcsVkcGMRSAiBvr6+\niggUi8Xg8/nQ19eHk5MTevToobKvjIwMbN68GbW1tdi+fTsGDhzYKYdInoWwsDDs378fhoaGKC4u\nhqurK7777jsMHDgQABAbG4s1a9bg0KFDGDt2LDgcDoqKisDj8bBmzRqEh4cjPT0dU6dOxdSpU7F/\n/35G/NvY2KCmpgaXL1/GwIEDabmWooBO41JeDPLy8qCrq8t4WgENE2zGxsbIy8tj+l4ANPtlfvv2\nbWzbtg2hoaEYNGhQmx93U5w5cwZz5swBi8XCiBEjUFlZiaKiIuTk5LTYu+tFxNHREb/99puKiG7L\nfkBt8vjxY0YgeXt7d7p+NeXJYOXzSwhhhkIePXqEBw8eQCaTMVFoly9fRkVFBQYPHgwTExNEREQg\nPT0d4eHhGDduXLcReRcuXEBQUBAsLS2xefNm+Pr6IicnBx988AE+/vhj7Nu3D05OTrh69Sr09PQw\nYcIEAA3+gl9++SWAhlgzqVQKT09PLF26FKGhobCxsUFZWRlOnz6NgwcPYvLkySrDTRRKS6Fij9Kl\nqa2tZZqglT26FMHpvXv3ZoTew4cPcfz4cYhEIrz00ksYO3asitN+aWkpTp8+jb179wJoKN22Rfns\naXYuBQUF6Nu3L/P/tra2KCgo0Ph4amqq1o+vq6JYWXoazeUFK/cDxsXFITw8XK0fUJv+gAqfOR0d\nnS5piKwwQy8vL4dQKMSAAQNgZmbGxMWVl5fjypUriIqKYnJ6/fz8GM86Ly8vlWGS5+Vp8WYnTpzA\nF198AUIIjI2NER0dzay6PWtaTn19Pc6dO4fKykqcPn0aY8aMAQDmd+utt97C/fv34eTkhMLCQjg7\nO6OkpAR79+5FZGQkPDw8EBcXp2IKvXDhQhQVFeHUqVPQ1dXFvn37MHny5Oc8O5QXGSr2KF2aiooK\nFBUVQSaTQSAQwNzcHNnZ2VixYgXMzMyYu+CjR49i5cqVcHNzY1I7xo4di++++w4ymQznzp3D7t27\noaenxwg8TUJPYZugo6Oj8kWflZXFhLE/bVWQ2rl0TlgsFszMzNrFH7C2thZ8Ph8SieS5Mng7EqlU\nipycHJSXl8PR0RHu7u7MZ0JHRwdcLheZmZlIS0vDggULsGTJEiaO8Pbt20hMTMRPP/3E9M9qg3nz\n5mHZsmVN5r46ODjgjz/+gJmZGRITE7Fo0SKVG6ZnScvp0aMHgoODceXKFXz11VcYM2YMCCEghGD8\n+PHgcDi4efMmJk+ejPHjx2PBggVwcXGBmZkZDhw4gJkzZ8LIyAhFRUWIj49HcHAwrKyssHfvXuTk\n5DATuBTK80DFHqVLU1ZWhqKiIuTm5sLb25sxTnZ3d8euXbtgb2+P+Ph4hIaG4s0338S2bdtgYGCA\n+Ph4rFixAl9++SVWr14NoVDI3Mn36tULXC4Xy5cvR0REBB49eoTy8nLY2Ngwd/6Aas6kQCDAr7/+\nii1btjR5rDU1NXj06BHjgdWUnUtTHl0SiaRJ7y5K26FNf8Ds7Gz89ttvGDx4MJycnLpk6oVcLkd+\nfj6z0tzYzkYul+Ps2bOIjIzEpEmTcPnyZWYFncvlYujQoRg6dGibHNvT4s0Uk7IAMGLECOTn52vl\n3x0yZAhmzJiBbdu24ffff2dK1P/++y/09PTg4uICoCGhZ8+ePRAKhYiLi4OnpyfkcjkePXqE48eP\nIzExERMmTGBWeKnQo2gLKvYoXZri4mLk5eXh8OHDmDZtGrKzsyGRSGBsbMxM98XGxsLGxga7d+9m\nLqKzZs1CQkICLl68iNWrV8PPzw9eXl6wsLDAiRMncOnSJaa8FBsbi0OHDiEnJwccDgdvvfUWPv74\nY5UG6YyMDJiamjZ7cf7f//6HwMBA/P333xgyZAiEQiEuXLiADRs2qDwvICAAUVFRCAoKQmpqKnr2\n7AkbGxtYWVlp9O56Xp5WvmqL0ld3oDX9gLm5uairqwPQYL7r5ubGPL+r9K0pTwlbW1tj2LBhKtO4\nhBD8+eef2LRpE9zc3PDLL7906puRw4cPq4j350nL0dXVxeTJk3Hu3Dls27YN48aNQ2JiIhYvXgxX\nV1eMGjUKhBBwuVxs27YNs2fPRlhYGCZOnAg2m41jx47hwYMH2LhxY7eZSqZ0LqjYo3RpCgoKIBKJ\nMHToUHC5XOZLFGhYYWCxWHj48CGuX7/OrLQMHjwYb775JkpKSqCnp8eYzgoEAgQEBMDExASTJk0C\nm83GkydP4OLigi1btsDS0hLp6enYt28fRCIRvvrqK3C5XMjlcty+fRs8Hk+lB7AxeXl5sLCwwNy5\nc5lm7ODgYLz++usqVjD+/v5ISEiAs7MzDAwMcOTIEQANXyhRUVGYOHEi493l6emplfPYXPmqLUpf\n3ZXG/YBCoRBfffUVTp06hWXLlsHV1RX379/Hzz//jK1bt7ZpP6A2qaioAJ/PR8+ePeHj46M2JXz3\n7l2EhYWBzWbj4MGDWvu9bCuSkpJw+PBhpKSkMI89b3vFgAEDEBQUhNDQUDg4OKCkpASLFy/Grl27\nVJ43adIkHDt2DPv378f+/fshFAoxePBgnDx5EjY2Nlp7jxSKMlTsUboshBAUFBTA2NhYZRJXgaK0\npPC0cnd3R3p6On7//XccPHgQlZWVmDVrFsRiMUpKSlBSUsKUl3R0dJiVLD8/P5SWlsLMzAy+vr6w\nsrLCZ599htTUVPj5+aG2thZ37tyBp6dnk/1aUqkU//77LzORx2KxVFZ13nvvPZV+wH379mncj7+/\nP/z9/bVx+lpMW5W+XgTS09NhZGSE1NRUcLlcAGDiroDOkRfcHNXV1cjMzASHw8GAAQPUpoQLCwux\ndetW8Pl8hIeHY9SoUZ1KpGoiPT0dISEhSExMVDFw1kZazoQJE5CUlITz58/jxo0bzM2nwhFA8Zmf\nMmUKJk6cyNjZ9O7dW3tvkELRABV7lC5LdXU10tLSwGazGQ89Td55Xl5e4HA4+OCDDwA0iEShUIjC\nwkLo6OhAX18fOTk5kMvlTHmSEAIdHR1cu3YNkZGRuHHjBgoKCmBiYoK+ffvi1q1bTAlLMVH52muv\nNXms9fX1uHv3Ljw9PVWOVSqVIi8vD5aWljA2Ntb4Ranshak4Lm3SmvKVNktfLwIvvfQSXnrppSa3\nt6YfkM/ng8PhtIs/YF1dHTIzMyGRSODs7KySAQs0JM7s3LkTFy9exPr16xEYGNglYuhyc3Mxffp0\nHD9+nOmjA9TTcjS1V7SE/v37IyAgAElJSUhKSoKbm5uK9ZPy55vD4YDD4XS5CWxK14SKPUqXxdDQ\nEKtWrUJxcTEAVVGkQE9PD/Pnz8eCBQswYsQI+Pv7w9jYGEBDeZLD4UAmk4HP58PY2BhWVlYAGr6E\n5XI5li9fjrKyMmzatAk2NjYoLi7GqVOncOPGDTg7OwNoKHGVlJQwhs6aqK6uRlZWFt5++21m/xkZ\nGdizZw+Sk5PB5/NhaWmJjRs3Yv78+cyXQuOerrZYNWlp+aotSl8UzXSUP6BYLEZ2djaqqqrg5OSk\nFl0mEonwzTff4NixY3j//fexbdu2NjUgby3K8Wa2trZq8WabN29GRUUF3n//fQBg+kxLSkrU0nKe\nNRbx1VdfxYQJExAREYGQkBBwOJwu1ZtJ6Z7QBA1Kt6C5i6lEIsGOHTvw9ddfw9raGp6enhCLxTA3\nN8fnn38ODoeDDz/8EGfPnkVubi7jr3fnzh0MHToUMTExjAeWWCzG1q1bsXPnTmbyNzExEW+88Qbu\n3LkDV1dXjcdw8+ZN+Pr64vz583j11Vchl8sxatQo5OfnY+XKlRg+fDji4+PxzTff4Mcff8TYsWMB\nACtXroRA00BlBAAADoZJREFUIMD69euRkZEBFouFUaNGNeueL5PJwGKxmPOh+G9VVRX4fD769u3L\niNrGhIWFwcjICGvWrFF5PD09HYGBgUhMTFRZEWnJaylty9Pygt3d3RkBqLAeavxZEYvFyM/PR2lp\nKezs7NC7d2+V58hkMsTGxmL37t2YPn06Vq9eTVekmiEuLg4ffvgh5syZgy1btqis7lEoWoYmaFC6\nP4qLaHN3zRwOB6tWrcLLL7+M5ORkPHz4EAYGBvD392d6kNzc3HD69Gns3LkT48aNw6BBg1BcXAw9\nPT0UFRUx+8rPz0d0dDQj6mQyGe7duwczM7Nm+26ys7PBYrHg5OQEAPjhhx/w119/oaCggGnKHjRo\nEJKSknDixAm88sor0NPTQ35+Pq5fv46VK1fC3Nwc//zzD9hsNv773/9i8ODBAP6/0K2vr0ePHj3U\nvlQU269du4bt27dj1apVmDx5MiQSCcRiMdLS0pCWlobXX39dY/mqrUtflOejpf6ABw8exP379yEW\ni+Hg4AB3d3e4ubnh1q1bOHfuHGJiYtRsVAghSEpKwpYtWzB06FBcuHBBqybI3RU/Pz+MGDEChw8f\nxrp16zpdIgrlBURh/tjCPxRKtyQ/P5+sXr2a9OrVi5iZmZHExEQiEonIxIkTibe3N/nxxx9JZGQk\n8fPzIywWiyxdupQQQkh9fT2ZP38+GTZsGJHL5U3uf+vWrcTGxoaIRCJSVVVFQkJCiIGBAfn+++9J\namoqkUgkhBBC9uzZQxwcHAghhNTV1ZHhw4cTMzMzcvr0aVJaWkru3r1LnJ2dib+/P5HJZMz+r1y5\nQl5//XViaWlJhg0bRq5fv05SU1PJ7du3mef9+OOPxNTUlGRmZhJCCJFKpYTP55M+ffoQHR0d0q9f\nPxIeHk5kMhmJjo4m0dHRhBBCFixYQExNTcnAgQPJwIEDyZAhQwghhPD5fOLt7U28vb2Jh4cHCQ8P\n18rPws7Ojnh5ean8W8okJSURExMT5ng2bdrEbEtMTCQuLi7EycmJbN++XSvH092QSCTk7t27ZPXq\n1aR3795k+PDhZMiQIWTo0KFk1qxZJDw8nJw+fZqcOXOGjB8/nsycOZM8ePCgow+7y3H37l1SWVnZ\n0YdB6f60SL9RsUd5YZDJZEQqlRKpVNqsMJNIJKSuro4Q0iCi3njjDWJpaUmmTJlCvvjiC8JiscjW\nrVsJIYRUVlaSl19+mSxcuLDJ/YnFYhIUFET8/PwIIYQUFhaSiRMnEgsLC+Lh4UG4XC7R0dEh1tbW\nhMPhEHt7e0IIIffu3SOurq5k3rx5Kvtbv349sbKyYv7/9u3bxMjIiPj4+JCvv/6arF+/nowfP54M\nGjSIDBgwgBBCyM6dOwmPxyNGRkZk165d5N9//yUikYgQQsi6deuIh4cHKSgoUDlXHYWdnR0pKytr\ncntSUhKZPHmy2uNSqZQ4OjoSPp9PRCIR8fb2Jnfu3GnLQ+2SiMViMmbMGPLee++RwsJCQgghcrmc\nCIVC8vfff5MjR46QlStXkv79+5OrV682+1l5Xt59911iZWVFPD09NW6Xy+Vk+fLlxMnJiQwYMIBc\nv36d2UaFPYVCCGmhfqNlXMoLQ3PTguT/bE8UWZ8Ki4uXX34ZZ8+eBdDQ1ySVSmFlZcVMWNbU1ODm\nzZuYMmVKk/uuq6tDRkYGY2FiY2ODqqoqBAUFISoqism9vXfvHv755x/0798fAMDn8yGXyzFixAgA\nDWU5ReaoonH+8ePH2LlzJ2xsbHD58mUYGBigpqYGn332GQ4dOoS33noLADB8+HCYm5tDKBQiOjoa\noaGhmDdvHqKiopCbm4uePXvC3NwcBQUF4PF4XWKysjFpaWlwdnZmbHiCgoJw5swZeHh4dPCRdS44\nHA5OnTql0repKS94586dbX4sT4s3S0xMREZGBjIyMpCamoolS5YgNTUVMpkMS5cuxW+//QZbW1v4\n+voiICCA/qwplCboeld0CqUNYLFYYLPZaiJHLpdDJpOBEAI9PT0YGBjg3XffZfyzeDwecnJysGTJ\nkib3XV5ejhs3bqgYzQ4dOhSpqam4desWeDwehg0bhrlz52L37t1YunQpgIZUDl1dXUa8KKxaHjx4\nwEwCZ2Zm4vr16wgMDISBgQHEYjGMjIwwadIk1NXVMT2CPB4PvXr1wujRo/HgwQPcuXOHmUwsKytD\nbW0tPv/8c7z00kswNTXFqlWrIJPJtHeCW4HCzmXIkCE4dOiQxuf8+eef8Pb2xqRJk3Dnzh0AYOK7\nFNja2qKgoKBdjrmr0dSATnvj5+fXbGTcmTNnMGfOHLBYLIwYMQKVlZUoKipSEfZ6enqMsKdQKJqh\nYo9CaQYdHR21AZDGIsjKyqrZ5Awul4spU6bA19eXeWzNmjXQ19fHJ598gqNHj+Ly5ctITEzEgQMH\nUFlZCaBByBkZGalEsNXU1ODhw4eMH2BRURGqqqpU9g0ApaWl6Nu3LxO9VFxcjOLiYsYepk+fPsxK\nXnZ2NioqKkAIwYULF7B27VocPnyYSe5ob1JSUnDz5k0kJiZi3759uHTpksp2Hx8f5ObmIj09HcuX\nL8e0adM65DgpbU9TAp4KewqldVCxR6G0ktZaKPB4PJw9exY+Pj7MY3Z2dti7dy9MTEywZs0aBAYG\nIiwsDPfv34ehoSEAMN57yjYrjx49QlFREQYNGgSgwWuwrKxMLU8zIyMDenp6zMpeQUEBHj9+zIg9\n8n+WSwKBAGVlZVixYgWTabp48WI4OTnh8uXLKs9tLzQlGShjYmLC2H74+/tDIpGgvLwcPB4PeXl5\nzPPy8/M7dTYrhUKhtBe0Z49CaWMU/YCNReLAgQPxww8/AGhI4SgqKoKpqSk4HA6EQiHq6urQp08f\nRvwBDeKsrq4O7u7uAAAvLy9IJBLcuXMHvr6+TGbpL7/8Aj09PabcW1hYCIlEwpSSFeXqrKwsmJiY\nYOTIkQAaVi0tLS3BZrNhYGAAoG2MnJuiJXYuxcXF6NWrF1gsFtLS0iCXy2FhYQFTU1NkZGQgOzsb\nPB4PMTExOHnypFaOy97eHsbGxmCz2YwRrzKRkZE4ceIEgAZT3nv37qGsrAzm5uZPfS2laZoS8BKJ\nhAp7CqUVULFHobQxin7Axsjlcib+zNjYmEn2ABpW7JKTk1FbW6vymoqKClhaWjJeZ1ZWVggMDMT6\n9ethbm4Oc3Nz7Nu3D+np6Rg3bhysra0BNJR7uVwuI/YUAygCgQCGhobMUIiOjg7EYjFyc3Px5ptv\naoyga0uaSjI4cOAAgIYUhNjYWERHR0NXVxf6+vqIiYlhBmuioqIwceJEyGQyzJ8/X6VP8nlJSkqC\npaWlxm1r167F2rVrAQDx8fHYtWuXSi9ac6+lNE1AQACioqIQFBSE1NRU9OzZEzY2NrCysmozYU+h\ndEeo2KNQOoiWiCjF6pqCoKAgBAUFqexj7969mDNnDgIDAzFs2DA4OztjwIABTGm3vr4eYrEYNTU1\nkEgkTLyVSCRCQUEBzMzMGCHCYrFQUlKCiooK9O/fv92nch0dHfHvv/+qPf7ee+8xf1+2bBmWLVum\n8fX+/v7w9/dvs+NrCT/88ANmzZrVocfQVXhavJm/vz8SEhLg7OwMAwMDpo+0rYU9hdLdoGKPQulC\nkEaxcMXFxdDV1UViYiJEIhHYbDZ+/vlnpKamMhYaPXr0wLhx43Dy5EkEBwdj9OjRePvttyEWi1Fe\nXs5M+ypW8R4+fAgdHR21PsAXGcWEMJvNxuLFi7Fo0SKNz6utrcX58+cRFRXV6te+iCjaGJqCxWJh\n3759Grd1BmFPoXQVqNijULoQCqGnEH03b95EbGwshgwZAl9fX/z777/49NNPMWTIEBXvvzFjxmDf\nvn04efIkTp48CS8vL1hYWODWrVtM7JpC7KWnp6NPnz5MCZjSMCHM4/FQWlqK8ePHw83NDX5+fmrP\ni4+PxyuvvKJSwm3paykUCqWtoGKPQumCKERf//79wWazsWnTJjx+/BimpqZ49dVXERoaqtKwrq+v\nj2nTpqnYlEgkEpw9e5YRJop9Xrp0Cfr6+jToXglNE8KaBFtMTIxaCbelr6VQKJS2gtVKW4X29WCg\nUCgtprq6GkVFRbCzs0OPHj3UtivMoXV0dJrtxSsqKkJZWRk8PT1bbTPTHWk8ITx+/Hhs2LABr7/+\nusrzqqqq4ODggLy8PGaCuqWvpVAolGekRXYJ1GePQukmmJiYwNXVVaPQA8BYfygLPU03ezY2NvD2\n9qZC7/8oKSnByJEjMXDgQAwbNgyTJ09mJoQVU8IAEBcXhwkTJqhY5TT1Wm1QWVmJGTNmwM3NDe7u\n7vjrr79UthNCsGLFCjg7O8Pb2xs3btxgtp0/fx6urq5wdnbG559/rpXjoVAonRe6skehUFRoPARC\n6ZzMnTsXo0aNQkhICMRiMWpra1WSXBISErB3714kJCQgNTUVH3zwAZMr6+LiopIr+8MPP9BcWQql\na0JX9igUSuuhQq/zU1VVhUuXLmHBggUAAD09PbXIPporS6FQFFCxR6FQKF2M7OxsWFlZ4d1338Xg\nwYMREhICoVCo8hyaK0uhUBRQsUehUChdDKlUihs3bmDJkiX4559/YGhoSHvvKBRKk1CxR6FQKF0M\nW1tb2NraYvjw4QCAGTNmqAxgAE3nyjb1OIVC6b5QsUehUChdjN69e6Nv37548OABAODixYtqAxYB\nAQE4duwYCCG4evUqkyvr6+vL5MqKxWLExMQgICCgI94GhUJpJ6ipMoVCoXRB9u7di9mzZ0MsFsPR\n0RFHjhxhrGBoriyFQlGmtdYrFAqFQqFQKJQuBC3jUigUCoVCoXRjqNijUCgUCoVC6cZQsUehUCgU\nCoXSjaFij0KhUCgUCqUbQ8UehUKhUCgUSjeGij0KhUKhUCiUbgwVexQKhUKhUCjdGCr2KBQKhUKh\nULoxVOxRKBQKhUKhdGOo2KNQKBQKhULpxvw/5NYLsm8WhSYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f899a6e5f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "def plot_3D_decision_function(ax, w, b, x1_lim=[4, 6], x2_lim=[0.8, 2.8]):\n",
    "    x1_in_bounds = (X[:, 0] > x1_lim[0]) & (X[:, 0] < x1_lim[1])\n",
    "    X_crop = X[x1_in_bounds]\n",
    "    y_crop = y[x1_in_bounds]\n",
    "    x1s = np.linspace(x1_lim[0], x1_lim[1], 20)\n",
    "    x2s = np.linspace(x2_lim[0], x2_lim[1], 20)\n",
    "    x1, x2 = np.meshgrid(x1s, x2s)\n",
    "    xs = np.c_[x1.ravel(), x2.ravel()]\n",
    "    df = (xs.dot(w) + b).reshape(x1.shape)\n",
    "    m = 1 / np.linalg.norm(w)\n",
    "    boundary_x2s = -x1s*(w[0]/w[1])-b/w[1]\n",
    "    margin_x2s_1 = -x1s*(w[0]/w[1])-(b-1)/w[1]\n",
    "    margin_x2s_2 = -x1s*(w[0]/w[1])-(b+1)/w[1]\n",
    "    ax.plot_surface(x1s, x2, 0, color=\"b\", alpha=0.2, cstride=100, rstride=100)\n",
    "    ax.plot(x1s, boundary_x2s, 0, \"k-\", linewidth=2, label=r\"$h=0$\")\n",
    "    ax.plot(x1s, margin_x2s_1, 0, \"k--\", linewidth=2, label=r\"$h=\\pm 1$\")\n",
    "    ax.plot(x1s, margin_x2s_2, 0, \"k--\", linewidth=2)\n",
    "    ax.plot(X_crop[:, 0][y_crop==1], X_crop[:, 1][y_crop==1], 0, \"g^\")\n",
    "    ax.plot_wireframe(x1, x2, df, alpha=0.3, color=\"k\")\n",
    "    ax.plot(X_crop[:, 0][y_crop==0], X_crop[:, 1][y_crop==0], 0, \"bs\")\n",
    "    ax.axis(x1_lim + x2_lim)\n",
    "    ax.text(4.5, 2.5, 3.8, \"Decision function $h$\", fontsize=15)\n",
    "    ax.set_xlabel(r\"Petal length\", fontsize=15)\n",
    "    ax.set_ylabel(r\"Petal width\", fontsize=15)\n",
    "    ax.set_zlabel(r\"$h = \\mathbf{w}^t \\cdot \\mathbf{x} + b$\", fontsize=18)\n",
    "    ax.legend(loc=\"upper left\", fontsize=16)\n",
    "\n",
    "fig = plt.figure(figsize=(11, 6))\n",
    "ax1 = fig.add_subplot(111, projection='3d')\n",
    "plot_3D_decision_function(ax1, w=svm_clf2.coef_[0], b=svm_clf2.intercept_[0])\n",
    "\n",
    "#save_fig(\"iris_3D_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training Objectives\n",
    "* Slope of a decision function equals a weight vector's **norm** (||w||)\n",
    "* Divide slope by 2 ==> any points where decision function = +1/-1 will be **2x away from decision boundary.**\n",
    "![example](pics/small-weight-vector-large-margin.png)\n",
    "* So we want minimal ||w|| to get max margins\n",
    "* If we also want zero margin violations, then decision function needs to be GT1 (positive) and LT1 (negative).\n",
    "* if soft margins OK - need to define a *slack variable* (C) for tradeoff."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quadratic programming\n",
    "* Hard- & soft-margin problems = convex quadratic optimization problems with linear constraints, ie *quadratic programming* (QP) problems. See [Convex Optimization for more info](http://goo.gl/FGXuLw)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### todo: The dual problem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### todo: Kernelized SVM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### todo: Online (incremental learning) SVMs\n",
    "\n",
    "* Linear SVM classifiers often use **SGD** to find a min-cost solution. SGD converges **much more slowly** than QP-based methods.\n",
    "* [implementation:](http://goo.gl/JEqVui)\n",
    "* [implementation:](https://goo.gl/hsoUHA)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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